Following a bench trial, the Superior Court of Henry County found Carlos Hall guilty beyond a reasonable doubt of possession of marijuana, OCGA § 16-13-30 (j); and obstructing or hindering a law enforcement officer in the lawful discharge of his official duties, OCGA § 16-10-24 (a). Hall appeals, contending the trial court erred in denying his motion to suppress marijuana that was seized during a consent search of a car in which he was a passenger. In alternative arguments, Hall contends that the arresting officer lacked a valid basis for initiating the traffic stop; that the driver’s consent to search was the product of an unreasonably prolonged detention; and that his objection to the search counteracted the driver’s consent. For the reasons explained below, we affirm.
On appeal from a ruling on a motion to suppress, we must construe the evidence most favorably to affirming the trial court’s factual findings and judgment. We accept the trial court’s factual and credibility determinations unless they are clearly erroneous, and the factual findings will be upheld if they are supported by any evidence. The trial court’s application of the law to undisputed facts, however, is subject to a de novo standard of review.
(Citation and punctuation omitted.) Peterson v. State, 294 Ga.App. 128, 129 (1) (668 S.E.2d 544) (2008).
At the hearing on Hall’s motion to suppress, the trial court received the following evidence. On July 22, 2008, an officer, who was monitoring southbound traffic on I-75 in Henry County, observed a 2008 Dodge Caliber hatchback traveling at between 60 and 70 mph and following another vehicle at a distance of less than half of a car length. The officer stopped the Caliber for following too closely, a violation of OCGA § 40-6-49. Mark Turner was driving, and Hall was his only passenger. Hall handed the officer a rental agreement for the Caliber, which showed that Kamara Awes rented the car in Florida with a planned return date of July 15, 2008.
As the officer began handling the traffic violation, he had difficulty hearing Turner’s responses, because Turner talked under his breath and because of noise from passing traffic. The officer asked Turner to step out of the car and then asked about his route that day. Approximately four minutes after the beginning of the traffic stop, the officer radioed his dispatcher to verify Turner’s license. While the officer waited for a report on the status check, he asked Hall his name and date of birth. Approximately eight minutes after the beginning of the stop, the officer asked Turner for his consent to search the car. Turner gave his consent, and the officer asked Turner and Hall to sit on the guardrail in front of the Caliber while he performed the search. During his search of the back seat, the officer smelled the odor of raw marijuana. The officer raised the back hatch and opened a box that was in the cargo area behind the back seat. He found ten pounds of marijuana that was packaged as a “brick” and encased in plastic. The report on the officer’s status check of Turner’s driver’s license came in about thirteen minutes after the beginning of the stop, about four minutes after the officer began searching the Caliber, and about one minute before he found the marijuana.
After finding the marijuana, the officer told Turner and Hall to place their hands on the car. Hall ran around to the driver’s seat, tried unsuccessfully to start the car, and then ran across the highway and into the woods, where he was apprehended.
1. Hall contends that, despite the officer’s testimony that he observed the violation of following too closely, the video recording of the traffic stop establishes as a matter of law that there was no traffic violation and, therefore, that the officer had no valid reason to pull the car over.  OCGA § 40-6-49 (a) defines the traffic violation of following too closely as follows: “The driver of a motor vehicle shall not follow another vehicle more closely than is reasonable and prudent, having due regard for the speed of such vehicles and the traffic upon and the condition of the highway.” Based on the officer’s testimony that his dashboard camera began to record after the truck that Turner had been following too closely had exited, and based on our own review of the recording, we conclude that the video recording of the traffic stop does not establish as a matter of law that the officer did not observe Turner following a vehicle more closely than was reasonable and prudent, having due regard for the vehicles’ speeds and the traffic conditions. Because the trial court was authorized to find that the officer observed the violation, and because a brief investigative stop of a vehicle is authorized whenever an officer observes a traffic offense,  the court did not err in denying Hall’s motion to suppress on this basis. Proctor v. State, 298 Ga.App. 388, 390 (1) (680 S.E.2d 493) (2009) (A traffic stop for following too closely was authorized where an officer observed a motorist driving on an interstate highway approximately one car-length away from the vehicle in front of him which led the officer to conclude, based on the speed and traffic conditions, that the motorist could not have avoided a collision if the leading car had braked abruptly.).
2. Hall contends that the officer prolonged the traffic stop beyond the time reasonably required to issue Turner a citation for following too closely and, therefore, that Turner’s consent to search was not valid.
“ The Fourth Amendment is not violated when, during the course of a valid traffic stop, an officer questions the driver or occupants of a vehicle and requests consent to conduct a search.” Salmeron v. State, 280 Ga. 735, 736 (1) (632 S.E.2d 645) (2006). The dispositive factor “is not the nature or subject of the officer’s questioning, but whether that questioning [takes] place during [an] otherwise lawful detention, ” such as, in this case, for committing a traffic violation in the officer’s presence. Id. In order to pass constitutional muster, the duration of a traffic stop cannot be unreasonably prolonged beyond the time required to fulfill the purpose of the stop. Sommese v. State, 299 Ga.App. 664, 668 (1) (683 S.E.2d 642) (2009). A reasonable time to conduct a traffic stop includes the time necessary to verify the driver’s license, insurance, and registration, to complete any paperwork connected with the citation or a written warning, and to run a computer check for any outstanding arrest warrants for the driver or the passengers. Id. at 669 (1) (b).
In this case, it is undisputed that the officer requested and obtained Turner’s consent to search before the officer received the verification of Turner’s driver’s license. Thus, the questioning and request for consent to search occurred before the purpose of the traffic stop was fulfilled. Salmeron v. State, 280 Ga. at 737 (1). Nor do we find any basis for concluding that the time that elapsed between the beginning of the traffic stop and the time the officer requested Turner’s consent to search, about eight minutes, was inherently unreasonable. Hall’s argument that the traffic stop was unlawfully expanded lacks merit. Id. at 737-739 (1).
3. Hall contends that he objected to the search of the Caliber and, therefore, that, even if Turner’s consent to search was valid, the officer lacked authority to search the car. It is undisputed, however, that Hall was not an owner or lessor of the Caliber. Furthermore, it is well settled that Turner, as the driver, had immediate control of the car and, therefore, authority to consent to a search.  Nor did the circumstances suggest that Hall had an exclusive interest in the box that would limit the scope of Turner’s general consent.  Accordingly, Hall’s argument that the search was unauthorized because he did not consent fails.
Andrews, P. J., and Doyle, J., concur.
 See Baker v. State, _ Ga.App. _ (1) (b) (Case No. A10A1039, ) (A passenger has standing to contest his or her own illegal seizure and detention in connection with a traffic stop and, therefore, to indirectly challenge the search of a vehicle in which he or she had no proprietary interest.).
 Proctor v. State, 298 Ga.App. 388, 390 (1) (680 S.E.2d 493) (2009); State v. Menezes, 286 Ga.App. 280, 282 (2) (648 S.E.2d 741) (2007).
 U.S. v. Matlock, 415 U.S. 164, 171-172, n. 7, (94 S.C. 988, 39 L.Ed.2d 242) (1974); U.S. v. Eldridge, 984 F.2d 943, 948 (V) (8th Cir., 1993); U.S. v. Dunkley, 911 F.2d 522, 526 (11th Cir., 1990); U.S. v. Morales, 861 F.2d 396, 399 (III) (3d Cir., 1988).
 See Florida v. Jimeno, 500 U.S. 248, 251-252 (111 S.C. 1801, 114 L.Ed.2d 297) (1991) (A driver’s general consent to search a car for drugs included consent to search a closed paper bag lying on the floor of the car.).
Contact a Douglasville, Ga lawyer for advice on any matter concerning search and siexure. This blog in no manner should be considered legal advice or by any means create an attorney-client privilege.


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The performance of underwater sensor networks (UWSNs) is greatly limited by the low bandwidth and high propagation delay of acoustic communications. Deploying multiple surface-level radio-capable gateways can enhance UWSN performance metrics, reducing end-to-end delays and distributing traffic loads for energy reduction. In this paper, we study the problem of gateway placement for maximizing the cost-benefit of this UWSN architecture. We develop a mixed integer programming (MIP) gateway deployment optimization framework. We analyze the tradeoff between the number of surface gateways and the expected delay and energy consumption of the surface gateway architecture in the optimal case. We used an MIP solver to solve the developed optimization problem and integrated the optimal results to serve as an input for our simulations to evaluate the benefits of surface gateway optimization framework. We investigated the effect of acoustic channel capacity and the underwater sensor node deployment pattern on our solution. Our results show the significant advantages of surface gateway optimization and provide useful guidelines for real network deployment.
An important component of oceanographic studies is the collection of data from the aquatic environment. Remote sensing has long been employed as a tool to collect aquatic data in underwater monitoring and exploration activities. Recently, in the last decade to be more specific, underwater acoustic sensor networks (UWSNs) have emerged as a new alternative technology enabling underwater monitoring and exploration applications, including scientific, commercial, and military applications [1–5]. Compared to their remote-sensing counterparts, UWSNs have many advantages. UWSNs can provide localized and more precise data acquisition. They can also employ a wider variety of sensors including, but not limited to, chemical, temperature, photo, and motion sensors.
UWSN technology is also replacing traditional underwater instrumentation technology. Traditionally, bulky sensor nodes equipped with data-storage capability are manually deployed in the underwater target space. Each node operates independently for the duration of the mission to collect readings according to a preset program. At the end of the mission, sensor nodes are picked up, and the collected data are retrieved and processed. UWSN technology adds networking capabilities to underwater sensor nodes so that sensor nodes can relay real-time data to an off-shore or even an on-shore control station for immediate analysis. The communication channel can also be used to transmit control signals from the control station to the underwater sensor nodes, which enables interactive control of the underwater sensor network deployment. UWSNs offer many advantages over traditional instrumentation techniques. First off, UWSNs add a real-time reporting functionality that enables a host of new real-time monitoring and warning systems. Another advantage of UWSN is that the sensing mission can be dynamically reconfigured without the need to physically access all the underwater nodes in order to reprogram them. While this particular feature makes the reuse of a UWSN deployment much less costly, it also provides for fixing configuration errors that compensates for unforeseen circumstances and unexpected node failures. This improves the UWSN resilience compared to traditional instrumentation techniques. Therefore, sensor node failures can be detected soon after they occur, allowing early replacement or early abortion of the mission instead of having to wait until the end of the mission only to find that it has failed.
In addition to the usual design challenges faced by terrestrial wireless sensor networks, UWSN technology has to deal with some unique challenges. It cannot use electromagnetic waves for long-range communication due to their quick absorption in water. Acoustic waves are usually considered the practical solution for UWSN communication. The dependency of UWSNs on underwater acoustic communications is particularly challenging. Factors such as the high levels of noise and the channel variability due to temperature, pressure, salinity gradients, and current-induced turbulence add more constraints to the already small bandwidth available for acoustic communication. Moreover, when the Doppler effect (due to mobility) is added to those factors, channel encoding becomes a crucial component to the success of underwater acoustic sensor networks. However, the most limiting factor of underwater acoustic communications is the extremely low propagation speed of sound, which is roughly 1.5 km/s, subject to slight changes due to pressure, temperature, and salinity variations . This is five orders of magnitude slower than the propagation speed of electromagnetic waves. Such high propagation delay can cause high end-to-end delay, which could be greatly limiting for interactive applications and other monitoring applications where response time is critical.
One way to mitigate the high propagation delay in acoustic communications is to deploy multiple surface-level gateways. In sensor networks, each sensor node can monitor and detect environmental events locally and then transfer these measurements through the network to a surface gateway node (also referred to as a sink in UWSNs), which then relays data to the control station. Unlike single-sink networks that use long underwater paths to reach the unique surface sink, in a multiple-sink underwater sensor network, as illustrated in Figure 1, underwater sensor nodes can send data packets toward their nearest surface gateway. A surface gateway then uses electromagnetic waves to forward the packets to the control station. Considering that electromagnetic wave propagation is in orders of magnitude faster than acoustic wave propagation, it is safe to assume that surface gateways can send packets to the control station in negligible time and with relatively small energy consumption since acoustic communications consume much more energy than radio communications . In this way, all the surface gateways (or sinks) form a virtual sink. Although architectures employing multiple surface gateway nodes were mentioned in [5, 7], there is no formal study on surface gateway deployment. Neither an analysis on the effect of using multiple surface gateways on the network energy consumption or delay characteristics has been conducted nor a guideline on the deployment of such a multi-sink architecture has been provided.
In this paper, we study the problem of surface gateway deployment and present guidelines for deciding the number and locations of surface gateway nodes given an underwater sensor network deployment scenario. We focus on optimizing the cost of surface gateway deployment, by finding the minimum number and the locations of surface gateway nodes required to achieve a given design objective, which can be communication delay, energy consumption, fault tolerance, or a combination of them. The surface gateway deployment problem is formulated as an optimization problem modeling the routing of data packets from underwater sensor nodes to the virtual sink under link capacity and flow conservation constraints. A variety of objective functions are presented. Our framework provides an optimal gateway selection from given gateway candidate locations which are assumed to be a given. The rest of this paper is organized as follows. In Section 2, we provide a review of related work. In Section 3, the network model and assumptions regarding the surface gateway deployment problem are presented and justified, and the surface gateway deployment problem is formulated as an optimization problem. In Section 4, we evaluate our work, choosing sample problems to analyze the effect of various constraints on the deployment solution quality, problem complexity, and feasibility. Finally, in Section 5, conclusions are drawn, and a future work is presented.
The deployment problem for sensor nodes was studied extensively for terrestrial sensor networks . The closest to our work from the placement strategies in terrestrial networks are those for relay node and multi-tier sensor network architecture [9–11]. However, most terrestrial deployment problems assume a static two-dimensional (2D) architecture, and not much attention was received for multi-gateway deployment in UWSN. A triangular-grid deployment pattern for 2D UWSN was proposed in . The objective is to minimize the number of sensors needed to achieve the sensing and communication coverage of a target area. An interesting attempt to formulate the 3D UWSN point-coverage deployment problem as an integer linear program (ILP) is presented in . The solution of the ILP decides relay node deployment, routing, and link scheduling. Throughout this work, it is assumed that there is a single sink for the entire UWSN deployment and only the overall power consumption is used as an optimization objective. Neither of these two studies considers the multiple-sink network architecture. The only research study in the frame of multiple sinks we found is , in which Seah and Tan investigated the use of multi-sink architecture to enhance the underwater sensor network reliability. In this study, the same message is directed to more than one of the multiple sinks, with the assumption that if any of the sinks gets the message, then it is considered delivered successfully. The simulation results showed that high-reliability benefits can be achieved at the cost of reasonable increase in energy consumption. The surface gateway (i.e., sink) deployment problem was not considered in this work. In a parallel research effort,  studied the problem of placing multiple mobile data collectors in both delay-tolerant and delay-constrained underwater acoustic sensor networks. The authors defined candidate data collection stations as the maximal overlapping regions (MORs) of surface circles corresponding to underwater node communication ranges. They developed an O(n2 logn) algorithm for finding MORs. An earlier work in  was the first to address the underwater surface gateway deployment problem and formulate it as an optimization problem. The problem of surface-level gateway placement has been addressed by later research effort in. The authors used surface gateways deployment as a mean to guarantee connectivity and survivability (tolerance to single node failure). They proposed an approximation algorithm for choosing a minimal subset of candidate locations where SGs may be deployed. An effort by the authors in  addressed the deployment for a mobile multiple-sink architecture in UWSN. They used a prediction-based deployment strategy to cater for the mobility of underwater nodes. However, our work differs from all above by formulating the problem to find the best candidate locations that satisfies a set of flow conservation constraints, interference constraints, number of gateway constraints, and performance constraints in addition to a set of delay and energy-consumption objectives.
There are two approaches to handle the surface gateway deployment problem, (1) solving the underwater deployment and the surface-level deployment problems jointly or (2) solving each of them separately. It is understood that solving both underwater and surface deployment problems jointly will lead to optimal solutions that are better, or at least as good as, the outcome of the two-phase approach. However, since the objective of the research presented here is to analyze the effect of surface gateway deployment on the overall underwater sensor network performance, we fix the underwater deployment and therefore opt for the latter option. Thus, we assume that there is a pre-existing underwater deployment that has been reached by a way or another.
The surface gateway deployment problem is formulated as a combinatorial graph optimization problem. The nodes of the graph represent underwater sensors and candidate surface gateway positions, and the problem is to find the subset of the candidate surface locations that maximizes a certain performance metric, satisfying a set of flow conservation constraints, interference constraints, and a deployment cost constraint (on the number of surface gateways) or a performance constraint (such as maximum end-to-end delay or minimum reliability level).
The selection of the candidate positions is sophisticated enough to be considered as a separate problem to on its own and is discussed by our work in . For the purpose of producing a generalized formulation, the set of candidate surface points is considered a given and assumed to satisfy connectivity constraints as a precondition. This means that each underwater node has to have at least one connected path to one or more candidate surface locations, taking into account the communication ranges of the involved intermediate nodes.
Associated with each underwater sensor node is a packet generation rate. Surface gateway nodes have to collect all generated data packets. The surface gateway deployment problem is formulated as a combinatorial optimization problem. The formulation consists of a basic set of constraints that can be augmented with a variety of objective functions.
The functionality of the UWSN considered is assumed to be mainly collecting data from underwater sensor nodes and transmitting the collected data samples at regular time intervals to a central station through one of the surface-level gateways. We assume that most of the traffic, therefore, will be flowing from the underwater nodes to the surface gateways. Inter-node communication (for purposes such as synchronization, collaborative sensing, data fusion, etc.) is assumed to be small enough to ignore.
Together, the set of surface-level gateways forms a virtual sink for the underwater sensors because the propagation delay, the energy consumption, and the reliability of transmitting the received packet by a gateway to the central station over a direct or multi-hop radio path are far superior to underwater communication links. It is reasonable, therefore, to assume that a packet delivered to one of the surface gateways is delivered to the central station with high reliability and negligible delay and energy cost.
For simplicity, we assume that the data link protocol uses only fixed-length packets and that all links have the same bit rate. Consequently, the packet transmission time is consistent throughout the network, and if the transmission scheme is slotted, the packet transmission time is conventionally called the timeslot. Our deployment formulation can be adjusted to include a variable packet length and a variable bit rate at different links without compromising the quality of the solution. This will require a pre-existing knowledge of these parameters which will increase number of inputs and will result in a more complex formulation of the flow constraints. However, we are interested in providing a more generalized formulation of the gateway optimization problem to be adjusted and tuned for a more specified application that may require varying some of the inputs we assume is a fixed.
The network is modeled as a graph, in which nodes represent the underwater sensors and surface gateways, and edges represent pair-wise communication links.
Let U be the set of all underwater sensor nodes and T be the set of candidate surface node positions.
V = U ∪ T.
where d(v,w) denotes the Euclidean distance between the two nodes u and v, and R u denotes the maximum acoustic communication range of the underwater node u.
E = e ( u , v ) : u ∈ U , v ∈ C u .
E u O = e ( u , v ) : v ∈ C u , ∀ u ∈ U.
E v I = e ( u , v ) : e ( u , v ) ∈ E , ∀ v ∈ V.
G = ∑ u ∈ U g u .
Let f e be the average flow per packet time in edge e measured in packets per packet time.
f v I = ∑ e ∈ E v I f e , ∀ v ∈ V.
f u O = ∑ e ∈ E u O f e , ∀ u ∈ U.
f t O = 0 , ∀ t ∈ T.
x t = 1 if a node deployed at t , 0 otherwise , ∀ t ∈ T.
Let T be the schedule length, i.e., the number of time slots in a single period of the schedule.
Let he,t be a binary variable that indicates whether link e is scheduled for transmission during slot t of the schedule.
h e u , v , t = 1 u transmits to v at timeslot t 0 , otherwise , ∀ u ∈ U , e ∈ E , 0 ≤ t < T.
The most important performance aspects of any network are the delay and energy-consumption characteristics.
Let υ be the average propagation velocity of sound waves in water.
τ u , v P = d ( u , v ) υ , ∀ u ∈ U , v ∈ V.
Let τ u Q be the average transmission queuing time including the expected channel access delay at node u.
τ u , v = τ u Q + τ + τ u , v P , ∀ u ∈ U , e ∈ E u O .
Let π e S be the transmission energy required for transmitting one data packet over the underwater acoustic link e(u,v), π L be the listening/sleeping average energy consumption per packet time, and π v R be the reception energy per packet. For surface gateways, the reception power is taken to include the energy required to forward a packet to the central station over radio.
π v = π L + π v R f v I + ∑ e ∈ E v O π e S f e , ∀ v ∈ V.
π v = π L + π v R f v I + π S f v O , ∀ v ∈ V.
n e = 1 − ρ e ρ e , ∀ e ∈ E.
π v = π L + ∑ e ∈ E v I π v R + n e π v R ′ f e + ∑ e ∈ E v O π e S + n e π e S ′ f e , ∀ v ∈ V.
π e u , v = π L f e + π e S + π v R + n e π e S ′ + π v R ′ .
The constraints can be classified into deployment constraints, flow conservation constraints, and interference constraints.
∑ t ∈ T x t ≤ N.
x t ∈ 0 , 1 , ∀ t ∈ T.
The scenario considered in this work will be a monitoring network, where instrumentation data flow from underwater sensor nodes and through the network to a common sink station. Therefore, the analysis is limited to the (possibly multi-path) route from each underwater sensor to the virtual sink. Control traffic flowing from the central station down to the underwater sensor nodes or inter-node traffic for the purpose of synchronization or localization or other functions than sensing data transfer will be ignored.
f t I ≤ x t G , ∀ t ∈ T.
This means that the total flow f t I into candidate gateway location t has to be zero if x t =0; otherwise, f t I can grow as large as the maximum potential flow in any link in the network which is equal to the total data generation rate G in the network, thus rendering the constraint void.
Flow conservation implies that for underwater sensor nodes, the sum of the average flows leaving a node equals the sum of the flows entering that node plus the local data generation rate.
f u O − f u I = g u , ∀ u ∈ U.
Flow conservation also implies that the total data generation rate of all underwater nodes must equal the total data absorption rate by the virtual sink composed of all surface gateways since each packet, generated by any source, must eventually be received by a surface node (before being relayed to the sink).
∑ t ∈ T f t I = G.
T · f e ≤ ∑ t = 1 T h e , t , ∀ e ∈ E.
Note that since we assume the schedule is periodic, there is no need to add a constraint to enforce the reception of a packet before sending it out. If a packet is sent before being received, this means that it was stored from the previous period. It follows that the maximum per-hop queuing delay will not exceed T−1 timeslots.
B ≤ 0 . 18 b.
I v = u : u ∈ U , d u , v ≤ R u I , ∀ v ∈ V.
f v O + ∑ u ∈ I v f u O ≤ B , ∀ v ∈ V.
This formulation is called pessimistic because that assumes that transmissions that could interfere with the reception at node v are going to happen in distinct time intervals without any overlapping. This is the worst case because it leaves the minimum possible bandwidth for v to receive its own intended transmissions. In reality, however, some of these transmissions from interfering neighbors of node v can occur simultaneously and successfully. Consider, for instance, two interfering neighbors of v, called u1and u2, v cannot receive any signals as long as it can hear either u1or u2 is transmitting. Now, if u1 and u2 are sending to w1 and w2, respectively, it is possible that both transmissions can succeed simultaneously if u1 is not within w2’s interference range and u2 is not within w1’s interference range.
∑ u ∈ I t f u O ≤ B , ∀ t ∈ T.
∑ e ∈ E v O h e , t ≤ 1 , ∀ v ∈ U , t ∈ 1 , … , T .
This means that a node cannot transmit on more than one link during the same time slot.
T is the number of time slots a packet spends waiting in the transmission queuing at any node. Since the queuing delay can vary from 0 up to T−1 time slots, we estimate L = T − 1 2 . In order to for this estimate to be accurate and in order to insure the best possible performance, a search for the minimum feasible schedule length will be necessary. We do so following the method pointed out in . Namely, we formulate the problem starting from T=2 and attempt to solve the MIP problem. As long as the MIP is infeasible, we continue to increase the schedule length T until we find the minimum T for which the ILP formulation is feasible.
The objective function determines the goal of the deployment optimization. In general, the objective can be (1) a collective measure, such as minimizing the average end-to-end delay and minimizing the total energy-consumption rate or (2) an extreme measure, such as minimizing the worst case end-to-end delay or maximizing the worst case node lifetime.
τ k i E = ∑ e ∈ k i τ e , ∀ u ∈ U , t ∈ T , k i ∈ K u , t .
E τ u , t E = ∑ k i ∈ K u , t f k i τ k i E ∑ k i ∈ K u , t f k u , t i .
f e = ∑ u ∈ U ∑ t ∈ T ∑ k i ∈ K u , t : e ∈ k i f k i .
δ e , k i = 1 , e ∈ k i 0 , otherwise .
f e = ∑ u ∈ U ∑ t ∈ T ∑ k i ∈ K u , t δ e , k i f k i .
where g u = ∑ t ∈ T ∑ k i ∈ K u , t f k i .
E τ E = ∑ u ∈ U ∑ t ∈ T ∑ k i ∈ K u , t f k i ∑ e ∈ k i τ e G = 1 G ∑ e ∈ E f e . τ e .
Minimize 1 G ∑ e ∈ E f e . τ e .
π k i E = ∑ e ∈ k i π e , ∀ u ∈ U , t ∈ T , k i ∈ K u , t .
E [ π E ] = 1 G ∑ e ∈ E f e . π e .
Minimize 1 G ∑ e ∈ E f e . π e .
When the optimization objective is to minimize the overall average end-to-end delay, some sources maybe excessively penalized with a much longer delay. In monitoring applications where uniform response time is favored, the optimization objective has to be minimizing the worst case, per-source average delay. In other words, the objective is to minimize the average delay observed by packets from each source taken separately, to guarantee the best possible worst case scenario. In order to define this objective, we define a set of new flow variables, fe,u to denote the portion of the flow in link e that is generated originally by node u. If no path from u to the virtual sink uses link e, this implies that fe,u=0.
τ u E = 1 g u ∑ e ∈ E f e , u τ e , ∀ u ∈ U.
τ u E ≤ U τ .
We conducted extensive simulation to evaluate our gateway deployment optimization framework. We assumed that acoustic transceivers of all nodes, both underwater nodes and surface gateways, to be homogeneous and, therefore, the communication range is assumed to be constant for all nodes. We assume that sensor nodes are either stationary or that their motion is correlated strongly enough to assume that their relative locations are fixed. We adopt the pessimistic interference model. To reduce the problem complexity, we assume a lightly loaded, i.e., such that channel access delays and queuing delays can be safely ignored. Since both channel access delay and queuing delay are functions of network load (i.e., flow), keeping the network very lightly loaded justifies the assumption that the queuing delay is constant, hence allowing the linearization of the formulation and the use of LP solvers. When the load is increased, the non-linear formulation can be solved similarly by piece-wise linearization algorithms, such as the Frank-Wolfe algorithm. Although the problem can be solved for a choice of optimization goals, we limit our focus on the simplest optimization goals, namely minimizing the average delay and minimizing the average power consumption. The LP solver uses a brute-force search algorithm to find the optimal gateway deployment locations by numerating all possible candidate solutions and checking whether each satisfies the problem’s statement.
In order to evaluate the benefits and the performance of the gateway deployment optimization techniques, we used the following simulation setting.
Throughout the experiments, we fixed the packet length L = 400 bits, the underwater acoustic propagation velocity υ = 1.5 km/s, and the transmission power is set to a constant of 1 W/s per packet time. The communication range for the underwater modems for all nodes is fixed at R C = 150. We also fixed the area of deployment to a square area of 600 m × 600 m horizontal extent and fixed the candidate gateway deployment positions to a 5 × 5 square mesh of points spaced 150 m apart.
The depth of all underwater sensors is arbitrarily set to 100 m, such that each of the underwater sensors, regardless of its horizontal location, is within the communication range of at least one surface gateway candidate position, thus satisfying the connectivity requirement. This guarantees that an optimal solution can be found by setting a large-enough limit on the number of surface gateway nodes, N. Finally, the data generation rate at each underwater sensor is set to 1 packet per second. The acoustic channel effective bit rate B is varied among 5, 10, and 50 kbps. Accordingly, the packet transmission time τ=80, 40, and 8 ms, respectively, and the data generation rate g= 0.08, 0.04, and 0.008 packets per packet time, and the energy consumption per packet transfer π S = 80, 40, and 8 W, respectively.
When the number of allowed surface-level gateway nodes increase, the performance characteristics, average delay or average power consumption, is expected to improve. To verify that, we vary the number of allowed surface nodes from 1 to 25 nodes and solve the optimization problem to get the optimal average delay or energy. Results show that an increase in the number of surface gateways can dramatically enhance performance, especially when the network is lightly loaded.
Intuitively, when the ratio of total data generation rate to the per-node channel bandwidth increases, the minimum number of surface-level nodes required to make the problem feasible increases. This is due to the fact that surface gateways will saturate with incoming traffic and, therefore, more nodes will be needed to handle the additional traffic corresponding to the increased data generation rate. On the other hand, increasing channel capacity reduces the network load, and consequently, our assumptions about ignoring queuing delays become more realistic. To demonstrate the effect of channel capacity on the quality of the solution, we solve the deployment optimization problem for different link capacities, namely 5, 10, and 50 kbps.
If the set of candidate surface gateway positions is preset, the locations of underwater sensors and the distribution of data generation load among them are expected to affect the benefit of adding more surface gateways. If underwater sensors are clustered in groups, less surface gateways are expected to feasibly route all traffic to the surface, compared to the case when underwater sensors are spread evenly over the deployment area. On the other hand, clustering increases the odds of collision and, in the case of high traffic loads, can negatively affect delay and energy consumption. To study the effect of the deployment scheme of the given set of underwater sensors on the result of the surface gateway deployment optimization, we use two underwater deployment patterns.
The uniform underwater deployment was chosen because the uniformity of the solution simplifies the process of verifying the results. The chosen underwater deployment consists of a 7 × 7 planar mesh of sensor nodes. The distance between two adjacent nodes is 100 m, and therefore, the nodes cover the entire 600 × 600-m area. This problem setting is illustrated in Figure 2.
It was similar to the uniform underwater deployment, except that the 49 underwater sensor nodes are distributed at random within the 600 × 600-m underwater area. This problem setting is illustrated in Figure 3.
Results show that an increase in the number of surface gateways can dramatically enhance performance, especially when the network is lightly loaded. For example, Figure 4 shows that the expected delay corresponding to B = 50 kbps can be reduced from 0.26 to 0.16 s using four surface gateways instead of one. It is also worth noting that the improvement gained by adding a surface gateway diminishes as the number of surface gateways increase. After a certain number of surface gateways, depending on underwater deployment and other factors, any additional surface nodes have negligible effect on the performance of the network. This is due to the fact that at that point, all underwater nodes communicate with the a surface gateway at the candidate position nearest to each of them, and therefore, further addition of surface nodes becomes redundant.
Average delay, uniform underwater deployment.
Simulation results show that the performance improvement resulting from the addition of more surface gateway nodes diminishes when the network load increases, confirming our expectations as explained before. For example, Figure 5 shows that the heavily loaded network, corresponding to the channel capacity of 5 kbps has a smaller dynamic range of 0.2/0.08 = 2.5 than the lightly loaded network corresponding to B = 50 kbps, whose dynamic range is equal to 1.2/0.8 = 1.5. Figures 4 and 5 show the effect of varying the channel capacity, in the case of uniform underwater deployment, on the expected delay and expected energy consumption, respectively. Figures 6 and 7 show the effect of varying the channel capacity in the case of random underwater deployment, on the expected delay and expected energy consumption, respectively.
Average energy, uniform underwater deployment.
Average delay, random underwater deployment.
Average energy, random underwater deployment.
Figures 8 and 9 compare the results of the uniform underwater deployment case and the random underwater deployment case at a fixed channel capacity of 10 kbps. When the number of surface gateways is small, the randomly distributed underwater deployment suffers more congestion and therefore performs slightly poorer than the uniformly distributed counterpart in both delay and energy-consumption metrics. When the number of surface gateways increases, the effect of congestion diminishes, and the effect of clustering grows stronger. After a certain number of surface gateways, the energy consumption of the randomly distributed underwater deployments converges to that of the uniformly distributed case because, eventually, each underwater node becomes one hop away from a surface gateway. Although Figure 8 shows that the delay of the randomly distributed case eventually becomes lower than the uniformly distributed case is not necessarily always true. The problem instance shown in Figure 3 happened to have an average distance between underwater nodes and candidate surface positions, lower than that in the uniformly distributed case in Figure 2, and therefore, the randomly distributed underwater deployment case exhibits less average propagation delay. The experiments were repeated for several random underwater deployments to confirm that the results exhibit the same trends. Figures 10, 11, 12 and 13 illustrate two more samples for the random deployment results.
Average delay, uniform vs. random underwater deployment.
Average energy, uniform vs. random underwater deployment.
Average delay, random underwater deployment experiment 2.
Average energy, random underwater deployment experiment 2.
Average delay, random underwater deployment experiment 3.
Average energy, random underwater deployment experiment 3.
In this paper, we provided a generalized optimization framework for the surface gateway deployment problem. We demonstrated how to use the formulation to find the optimal placement of surface gateways with respect to a variety of optimization goals and a set of flow conservation constraints, interference constraints, and deployment constraints. We assisted our work by incorporating the optimal gateway optimization framework results in simulating the operation of the UWSN with multiple surface gateways. Our simulation results confirmed the potential for performance improvement using multiple surface gateways, such as reducing both average delay and energy consumption. It was also shown that the effect of the added surface gateways depends on the channel capacity or the network loading level, as well as the given underwater sensor deployment pattern. Our work presented here helps to pave the way for a wide variety of future research. One possible improvement is to optimize underwater and surface deployments jointly. Another is to consider mobility of surface gateways and a static UWSN with some level of location certainty models and integrate it as a new design parameter in our framework.
This work is supported in part by the US National Science Foundation under CAREER grant nos. 0644190, 1018422, 1127084, 115213, and 1205665.

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Regular and special legislative sessions for the majority of states have come to an end. Many states used their sessions to address this year’s biggest question—to conform or not to conform to the 2017 federal tax act (Pub. L. No. 115-97). Other states chose to continue conforming to prior versions of the Internal Revenue Code, and yet others chose to keep rolling and conform to the current version of the code.
California is the only non-rolling conformity state still in regular session that has not yet passed legislation adjusting the general conformity date. A.B. 2855, which conforms to the 2017 tax act, is still alive and in the hands of the Committee on Appropriations. The state is expected to take action prior to the end of the legislative session on Aug. 31. As we wait for the Legislature’s decision, let’s take a quick look at what the rest of the states accomplished in their legislative sessions.
Thirteen states took initiative to conform to all or part of the 2017 tax act by passing legislation with a conformity date on or after Dec. 21, 2017, the date of the 2017 tax act’s passage. These states include: Florida, Georgia, Hawaii, Idaho, Indiana, Iowa (for tax years beginning in 2019), Kentucky, North Carolina, Ohio, Vermont, Virginia, West Virginia, and Wisconsin.
Six states continue to conform to versions of the code in effect prior to tax reform, including above mentioned California, Maine, Minnesota, New Hampshire, South Carolina, and Texas. Arizona became the only state that updated its conformity date with a date prior to federal tax reform. Arkansas, Mississippi, and New Jersey have no general conformity, and the remaining states have rolling conformity to the current version of the code.
States have also taken differing approaches on the 2017 tax act’s “hot button” provisions: global intangible low-taxed income (GILTI) and foreign derived intangible income (FDII) (I.R.C. §§ 250 and 951A), the qualified business income (QBI) deduction (I.R.C. § 199A), and repatriation of foreign income (I.R.C. § 965).
On the GILTI and FDII front, Idaho, North Carolina, Virginia, and Wisconsin have decoupled from both provisions; Georgia and Indiana decouple from the GILTI provisions, and New York decouples from the FDII provisions. Hawaii has decoupled from I.R.C. § 250, but conforms to I.R.C. § 951A, while Illinois does the opposite, specifically adopting the GILTI provisions of I.R.C. § 250, but decoupling from I.R.C. § 951A.
For the QBI deduction, Georgia, Hawaii, Kentucky, Oregon, Virginia, and Wisconsin have specifically decoupled from I.R.C. § 199A, while Iowa will require a partial addback of any income deducted for tax years beginning in 2019.
The new provisions on repatriation of foreign income have been arguably the most confusing aspect of tax reform, and they are a concern for static conformity and rolling conformity states alike. Repatriation has accordingly received the most attention from the states, with 18 states so far issuing guidance on how to calculate income under I.R.C. § 965 for state purposes. These states are Alabama, California, Colorado, Connecticut, Georgia, Florida, Idaho, Illinois, Indiana, New Jersey, New York, Oregon, Pennsylvania, Rhode Island, Tennessee, Utah, Vermont, and Wisconsin.
Seven months post-tax reform, states continue to address the ripple effect of federal changes at the state level. With most legislative sessions adjourned, states may not be able to pass legislation, but taxpayers should continue to be on the lookout for official guidance.
Continue the discussion on Bloomberg BNA’s State Tax Group on LinkedIn: As California’s legislative session comes to a close, how do you expect the state to address the 2017 tax act?
For more information on the impact of Pub. L. No. 115-97, examine Bloomberg Tax’s Tax Reform Roadmap, showing detailed comparisons between pre-reform law and impending changes, with pertinent cites attached.


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IP practice around Europe is at its most inconsistent when it comes to Supplementary Protection Certificate (SPC) protection for second and further medical indication inventions. A recent Opinion of the Advocate General at the CJEU may point to a pending harmonisation of practice in this area but in a direction that will dismay applicants with inventions in this area.
Supplementary Protection Certificates are “patent term extension” rights which are granted to patent owners with products that require regulatory approval before they can be marketed. Human medicines are the most obvious example, although the system also applies to veterinary medicines and certain agrochemicals. Because patents have a fixed, 20-year, duration, SPC rights are granted as a compensation for the patent term which can effectively be wasted waiting for marketing approval of a product.
d) The authorisation referred to in point b) (that covering the product) is the first authorisation to place the product on the market as a medicinal product.
For this purpose, the “Product” is interpreted as being an active agent such as a drug compound. A strict interpretation of Art 3(d) would permit an SPC to be granted only the first time a specific active chemical was marketed, whether that was used for human medicine or in animals. This would reward the development of new active chemicals but not new uses of known materials.
A relatively strict interpretation of the SPC regulation was the norm until 2012 when the “Neurim” referral to the CJEU (C-130/11) changed the landscape significantly. Neurim had developed a product for treating insomnia in humans using the hormone melatonin. However, melatonin had previously been authorised for use in sheep which meant that the UK IPO disallowed Neurim’s SPC application on the basis of Art 3(d) above (the human marketing authorisation was not the first). Neurim appealed and ultimately the CJEU judged that they should be allowed an SPC to compensate for the time spent achieving regulatory approval for their product. In the judgement, the CJEU indicated that an earlier marketing authorisation could be ignored if it did not cover anything protected by the patent that was relied on for the new drug. This was a major departure from previous practice and resulted in several patent offices around Europe (including Germany and France) beginning to grant SPCs for new medical uses of old drug compounds (so-called second medical indication inventions). Thus, if a headache medicine was found to protect against heart disease then not only could that discovery be patented but an SPC granted to extend that patent if the need to obtain regulatory approval delayed it reaching the market.
The Neurim decision resulted in many but not all European countries changing their practice on second medical use SPCs with some granting them routinely and others, including the UK, remaining unconvinced. Now, however, a new referral is before the CJEU and looks set to reverse the liberalisation of SPCs seen in Neurim.
This case is another referral to the CJEU (C-443/17) from the English courts, since the UK IPO maintains its practice of interpreting Art 3(d) strictly, and relates to a SPC application by Abraxis for their new formulation of the anti-cancer drug paclitaxel. Paclitaxel is a known drug agent so Abraxis’ invention and patent are limited to the new protein-bound nanoparticle formulation that they have developed. They argue that because of this, their patent does not cover any medicine previously authorised and so they should be entitled to an SPC on the basis of the Neurim Judgement.
We only have the opinion of the Advocate General (AG) so far, which is advisory to the court but does not bind it in any way. However, the AG is absolutely savage about the decision in Neurim, setting out why he considers that the court should not have the power to decide as they did in Neurim, why that judgement was based on policy rather than on law and why even that policy may not be a good one. This opinion may not be binding but if the court accepts any of the lines of reasoning set out by the AG then practice on SPCs for second medical indications is likely to be tightening sharply.
4) The court overturns Neurim and reverts to the position that any prior marketing authorisation will negate all possibility of an SPC on a new invention.
The AG is clearly in favour of option 4) and makes a strong case for that. It’s possible that the court might go for option 3), however, since that would allow them to paint Neurim as a special case without having to actually overturn the earlier judgement. Option 1) would only be possible if the court were to completely reject the AG’s Opinion and all of the reasoning within it. That’s possible but highly unlikely. In any case, if the court can decide clearly on any one of the options above then we will have much more certainty on the interpretation of this article and practice around Europe may begin to unify again. Watch out for the judgement in the next few weeks.

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In the broadest sense, civil rights might be described as those rights which we grant one another in a civil society. These are rights designed to promote the general welfare and civility of a group of people living together in an organized society. Importantly, like Lady Justice herself, these rights might be perceived by the governed as blind to the improper influence of power or corruption – providing rights to the minority as well as the majority – allowing the society to exist together with a unifying fabric of rights.
Among those civil rights which might be important in our daily life, but perhaps overlooked or taken for granted in “modern” times, is the civil right which we have freely and voluntarily given to ourselves – the civil right to pursue a civil action against our own government for wrongs caused by the government. Without this important civil right, the governed might find themselves disconnected from the exercise of power and its consequent responsibility, and instead perceiving a double standard between what we expect of one another in conducting our daily lives, versus what we can expect from our government.
In Kansas, the civil right to pursue an action against our own government for wrongs caused by the government is codified by the Kansas State Legislature in K.S.A. 75-6101 et seq, labeled the Kansas Tort Claims Act.
As set forth in A Selection of Legal Maxims, by Herbert Broom, Esquire, in 1845, “It is an ancient and fundamental principle of the English constitution that the king can do no wrong.” Under this principle, the sovereign is not amenable to suit.
When the American states united and broke free from the authority of the crown, the concept of federal sovereign immunity was not specifically mentioned in the United States Constitution. Under Article III, Section 2 of the United States Constitution, “The judicial Power shall extend to . . . to Controversies . . . between a State and Citizens of another State . . . .” Arguably, the United States Constitution, by its apparent plain language, allowed the federal courts to hear cases between a state and citizens of another state, thus eliminating state sovereign immunity. Within a few years following ratification of the Constitution, Alexander Chisolm sued the state of Georgia in the United States Supreme Court for debts incurred during the Revolutionary War. The State of Georgia did not appear, and the plaintiff asked the Court to enter a show cause order for Georgia to appear and show cause why judgment should not be entered against it. Before entering the order, the Court indicated that “it is proper that this Court should be satisfied it hath cognizance of the suit.” Chisolm v. Georgia, 2 U.S. 419, 429 (1793).
Following a discussion of sovereign immunity and the presence of English common law in early American jurisprudence, the United States Supreme Court concluded that by the language of Article III, Section 2, the Constitution allowed the sovereign states to be sued in court.
With the absence of any override to federal sovereign immunity in the United States Constitution, as well as the passage of the Eleventh Amendment, sovereign immunity continued to remain the law of the land throughout the next century and a half.
Beginning early in the twentieth century, however, Congress began to reconsider federal sovereign immunity. The Federal Tort Claims Act was passed by the Seventy-ninth Congress in 1946 as Title IV of the Legislative Reorganization Act, 60 Stat. 842, after nearly thirty years of congressional consideration. Dalehite v. United States, 346 U.S. 15, 24 (1953). It was the offspring of a feeling that the Government should assume the obligation to pay damages for the misfeasance of employees in carrying out its work. Dalehite, 346 U.S. at 24.
By the mid-twentieth century, with the enactment of the Federal Tort Claims Act, federal sovereign immunity for tort claims had eroded, and it was officially recognized that at least with respect to the United States Government, the king could do wrong.
Meanwhile, throughout much of the twentieth century, in the courts in the State of Kansas, sovereign immunity persisted with respect to the state itself, its counties, and its municipalities. Woods v. Kan. Tpk. Auth., 205 Kan. 770, 770-71, 472 P.2d 219, 220 (1970), Caywood v. Bd. of County Comm’rs, 194 Kan. 419, 421-23, 399 P.2d 561, 562-64 (1965), and Jones v. City of Kansas City, 176 Kan. 406, 408-09, 271 P.2d 803, 805-06 (1954).
For a time, the Kansas courts and Kansas legislature battled the limits of the fundamental fairness of the doctrine of sovereign immunity. The Kansas Supreme Court rendered five decisions between 1969 and 1979 on the issue of governmental immunity, four of which abrogated governmental immunity, either partially or completely. Kansas Legislator Briefing Book (2015). Finally, in 1979, the legislature officially waived sovereign immunity in the State of Kansas with the passage of the Kansas Tort Claims Act. K.S.A. 75-6101 to 75-6120. It has been noted that the Kansas Tort Claims Act is patterned after the Federal Tort Claims Act. Westerbeke, The Immunity Provisions in the Kansas Tort Clams Act: The First Twenty-Five Years, 52 Kan. L. Rev. 939, 960 (2003).
The origins of sovereign immunity appear to be based in part on the infallibility of the monarch, but nonetheless, the doctrine persisted for a time in this country. There is no question that shielding the government from some wrongs, while allowing redress for other wrongs, seems fundamentally unfair, especially to victims who did not choose their wrongdoer.
Each governmental entity shall be liable for damages caused by the negligent or wrongful act or omission of any of its employees while acting within the scope of their employment under circumstances where the governmental entity, if a private person, would be liable under the laws of this state.
[T]he most serious threat to a broadly based system of governmental liability for damages caused by tortious conduct . . . is the KCTA’s express retention of a series of specifically enumerated exceptions set forth in section 75-6104. Initial drafts of the KCTA preserved immunity for only a limited number of fundamental government functions. Yet before the legislation was final, the Kansas League of Municipalities successfully convinced legislators to add a number of additional immunities. In the twenty-five years since enactment, the KCTA has been repeatedly amended to add new immunities, and today the KCTA contains twenty-five specific immunities.
Westerbeke, The Immunity Provisions in the Kansas Tort Clams Act: The First Twenty-Five Years, 52 Kan. L. Rev. 939, 945-46 (2003).
- A limit of $500,000 for any number of claims arising out of a single occurrence or accident, unless insurance has been purchased. K.S.A. 75-6105(a) and 75-6111(b).
- No punitive or exemplary damages, except for acts or omissions of employees because of actual fraud or actual malice. K.S.A. 75-6105(c).
- Allowing payment of judgments by periodic payments. K.S.A. 75-6112.
- Excepting certain health care providers from the Act. K.S.A. 75-6115.
- Providing a framework for defending and indemnifying employees for claims based on violations of the civil rights laws of the United States or of the state of Kansas. K.S.A. 75-6116.
- Establishment of a tort claims fund in the state treasury, administered by the Attorney General. K.S.A. 75-6117.
- Excepting members of: any governing body of a municipality, appointive board, commission, committee, or council. K.S.A. 65-6119.
- Discussing the actions of charitable health care providers. K.S.A. 75-6120.
Under K.S.A. 12-105b(d), a notice of claim must be filed with the clerk or governing body of the entity prior to the filing of the claim.
Under K.S.A. 12-105a, a “municipality” means and includes county, township, city, school district of whatever name or nature, community junior college, municipal university, city, county, or district hospital, drainage district, cemetery district, fire district, and other political subdivision or taxing unit, and including their boards, bureaus, commissions, committees and other agencies, such as, but not limited to, library board, park board, recreation commission, hospital board of trustees having power to create indebtedness and make payment of the same independently of the parent unit.
Under K.S.A. 75-6102(c), a municipality includes any county, township, city, school district or other political or taxing subdivisions of the state, or any agency, authority, institution, or other instrumentality thereof.
The notice requirement does not apply to the state itself and its agencies.
(5) a statement of the amount of monetary damages that is being requested.
In the filing of a notice of claim, substantial compliance with the provisions and requirements of this subsection shall constitute valid filing of a claim. The contents of such notice shall not be admissible in any subsequent action arising out of the claim.
Once notice of the claim is filed, no action shall be commenced until after the claimant has received notice from the municipality that it has denied the claim or until after 120 days has passed following the filing of the notice of claim, whichever occurs first.
A claim is deemed denied if the municipality fails to approve the claim in its entirety within 120 days unless the interested parties have reached a settlement before the expiration of that period. No person may initiate an action against a municipality unless the claim has been denied in whole or part.
Any action brought pursuant to the Kansas tort claims act shall be commenced within the time period provided for in the code of civil procedure or it shall be forever barred, except that, a claimant shall have no less than 90 days from the date the claim is denied or deemed denied in which to commence an action.
“Against a municipality” - The jurisdictional bar in K.S.A. 2013 Supp. 12-105b(d) unambiguously applies only to lawsuits against municipalities. Failure to comply with the statute does not deprive a district court of jurisdiction over a lawsuit against a municipal employee. Whaley v. Sharp, 301 Kan. 192, 201, 343 P.3d 63, 69 (2014).
“Clerk or governing body” - K.S.A.2011 Supp. 12-105b(d) requires a notice of claim against a county to be served on the county clerk or the board of county commissioners. Here, there is no evidence in the record that Huehl furnished a written notice of claim on either the clerk or the board of county commissioners. Because Huehl failed to provide written notice of his claim as required by K.S.A.2011 Supp. 12-105b(d), the trial court lacked jurisdiction over his claims against the defendants. As a result, the trial court properly dismissed the case with prejudice. Huehl v. Board of County Com’rs of County of Lincoln, 298 P.3d 1139 (Kan. App. 2013); see also Meara v. Douglas County, 293 P.3d 168 (Kan. App. 2013); Steed v. McPherson Area Solid Waste Utility, 43 Kan.App.2d 75, 221 P.3d 11 (2010); and Orr v. Heiman, 270 Kan. 109, 114-15, 12 P.3d 387 (2000) (filing with school superintendent complied with clerk requirement); Smith v. Kennedy, 26 Kan.App.2d 351, 361, 985 P.2d 715, rev. denied 268 Kan. 848 (1999) (filing with CEO of entity complied with clerk requirement).
When considering whether a notice substantially complies with the requirements found in K.S.A. 2014 Supp. 12-105b(d), the Kansas Supreme Court has held that "substantial compliance means ‘compliance in respect to the essential matters necessary to assure every reasonable objective of the statute.’ 297 Kan. at 775 (quoting Dodge City Implement, Inc. v. Board of Barber County Comm'rs, 288 Kan. 619, 639, 205 P.3d 1265 ). Further, "the question of compliance is not based upon a 'mechanical counting' of information addressing each enumerated category in the statute. Instead, notice is sufficient if it gives the municipality what it needs for a 'full investigation and understanding of the merits of the claims advanced.' [Citations omitted.] This is achieved when the notice advises the municipality of the time and place of the injury, affords the municipality an opportunity to ascertain the character and extent of the injury sustained, and allows for the early investigation and resolution of claim disputes. [Citation omitted.]" Sleeth v. Sedan City Hospital (Sleeth II), 298 Kan. 853, 865, 317 P.3d 782 (2014).
“Until after . . . 120 days” - We hold that the 120-day review period requirement of K.S.A. 2012 Supp. 12-105b(d) establishes a statutory condition precedent that must be met before a court has subject matter jurisdiction over a claim against a municipality under the Kansas Tort Claims Act. Its time constraint may be shortened only if a municipality acts to deny the claim in whole or in part before a petition is filed in the district court. The 120-day review period cannot be waived to give a court subject matter jurisdiction over a prematurely filed lawsuit. Sleeth v. Sedan City Hosp., 298 Kan. 853, 871, 317 P.3d 782 (2014).
VI. What Is Not Covered by the Kansas Tort Claims Act.
Babbs v. Block, Case No. 15-00194-CV-W-HFS (W.D. Mo. Mar. 10, 2016) (dismissing plaintiff’s complaint) (“The dispositive issue for me is comity, that is, whether Kansas governmental immunity law should be applied when the alleged injury occurred in Missouri.”) In Babbs, a Kansas police officer entered Missouri bar with his weapon, consumed several alcoholic beverages, flashed his weapon, was asked to leave, was escorted out of the bar by plaintiff (who was a security guard) and others, and in the process, his weapon went off, striking plaintiff in the torso. The Missouri federal court used comity to apply Kansas law.
Patterson v. Cowley County, 388 P.3d 923 (Kan. App. 2017) – SUV with two intoxicated passengers drove into Arkansas River after travelling down an road within a recreation area; an action was brought under the Kansas Tort Claims Act. The Court of Appeals discussed various immunity exceptions to the Act, and allowed the case to proceed on the grounds that the recreational use immunity exception did not apply to the County.
Cullison v. City of Salina, 371 P.3d 374 (Kan. App. 2016) – 12-year old slipped and fell and was electrocuted on exposed electrical junction box, causing her death. The Court of Appeals also discussed the recreational use exception, allowing the case to proceed.
Keiswetter v. Kansas, 304 Kan. 362, 373 P.3d 803 (2016) – Inmate escaped while on a work detail, hid during the search, entered a woman’s house at night to attempt to steal her car keys, and encountered the woman, kicking her, causing her to fall and hit her head, and as a result, she passed away. The Supreme Court of Kansas held that the State was entitled to summary judgment because it was immune from liability under the KCTA’s police protection exception.
One final practice point – as suits against the government often involve both violations of federal laws as well as state torts, remember that federal courts may accept ancillary jurisdiction over the state law claims, and there will be federal decisions interpreting the Kansas Tort Claims Act.

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