This paper introduces a protocol that distributively constructs a collision-free schedule for multi-hop packet radio networks in the presence of hidden terminals. As a preliminary step, each wireless station computes the schedule length after gathering information about the number of flows in its neighbourhood. Then, a combination of deterministic and random backoffs are used to reach a collision-free schedule. A deterministic backoff is used after successful transmissions and a random backoff is used otherwise. It is explained that the short acknowledgement control packets can easily result in channel time fragmentation and, to avoid this, the use of link layer delayed acknowledgements is advocated and implemented. The performance results show that a collision-free protocol easily outperforms a collision-prone protocol such as Aloha. The time that is required for the network to converge to a collision-free schedule is assessed by means of simulation.
To further complicate the issue, wireless propagation introduces an additional degree of randomness and unpredictability to the network. In order to advance in the analysis of multi-hop packet radio networks, some simplifications are in order. One of the most common modeling assumptions is the use of a graph representation of the network, where an edge exists between two stations if they are in the transmission range of each other. As an example, @cite_28 uses a graph representation to show that determining whether a traffic matrix belongs to the capacity region of a packet radio network is NP hard. We will use the graph topology representation and several other assumptions in the present paper.
@cite_28
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In this paper, we consider CSMA policies for scheduling packet transmissions in multihop wireless networks with one-hop traffic. The main contribution of the paper is to propose a novel CSMA policy, called Unlocking CSMA (U-CSMA), that enables to obtain both high throughput and low packet delays in large wireless networks. More precisely, we show that for torus interference graph topologies with one-hop traffic, U-CSMA is throughput optimal and achieves order-optimal delay. For one-hop traffic, the delay performance is defined to be order-optimal if the delay stays bounded as the network-size increases. Simulations that we conducted suggest that (a) U-CSMA is throughput-optimal and achieves order-optimal delay for general geometric interference graphs and (b) that U-CSMA can be combined with congestion control algorithms to maximize the network-wide utility and obtain order-optimal delay. To the best of our knowledge, this is the first time that a simple distributed scheduling policy has been proposed that is both throughput utility optimal and achieves order-optimal delay. Packet radio networks are modeled as arbitrary graphs by most researchers. We show that an arbitrary graph is an inaccurate model of the radio networks. This is true because there exists a large class of graphs which will not model the radio networks. Radio networks can be modeled accurately by a restricted class of graphs called the planar point graphs. Since the radio networks can accurately be modeled only by a restricted class of graphs, the NP-completeness results for scheduling using an arbitrary graph as the model, do not correctly reflect the complexity of the problem. We study the broadcast scheduling problem using the restricted class as the model. We show that the problem remains NP-complete even in this restricted domain. We give an O(nlogn) algorithm when all the transceivers are located on a line. We restrict our attention to static allocation in general and TDMA in particular. However, it may be noted that the results presented are also valid for other static allocation schemes. A selection problem is among the basic communication primitives in networks. In this problem at most k participating stations have to broadcast successfully their messages. This problem is especially important in packet radio networks, where simultaneous transmissions of many neighbors result in interference among delivered messages. This work focuses on a single-hop radio networks with n-stations, also called a multiple access channel, and considers both static and dynamic versions of the selection problem. We construct a family of efficient oblivious deterministic protocols based on selectors, one of them with selection time cO(klog(n k)), and the second explicit construction with selection time cO(k polylog n). The first construction matches the lower bound Ω(klog(n k)) on deterministic oblivious selection, while the second one is the first known explicit construction better than Θ(k2). In the dynamic case we introduce the model of dynamic requests, called k-streams, which generalizes the static model and the dynamic requests with at most k participants. We prove that each oblivious deterministic protocol has latency Ω(k2 log k), and on the other hand we prove the existence of the oblivious deterministic protocol with latency cO(k2log n). In view of the existence of the randomized oblivious protocol with expected latency cO(klog(n k)), this shows that randomization is substantially better than determinism for dynamic setting. Selection problem can be applied to implement other communication primitives --- we demonstrate it in the example of broadcast problem in multi-hop ad-hoc radio networks. In particular, we design an adaptive deterministic protocol broadcasting in time cO(nlog D) in every D-hop radio network of n-stations. The design of packet radio networks involves a large number of issues which interact in a very complex fashion. Many of these pertain to the RF channel and its use, others pertain to the operational protocols. Clearly, no single model can be formulated which incorporates all the necessary parameters and leads to the optimum solution. The one essential element which complicates matters is that, contrary to point-to-point networks in which each channel is utilized by a single pair of nodes, the radio channel in packet radio networks is a multiaccess broadcast resource: i) in a given locality determined by radio connectivity, the channel is shared by many contending users, hence the need for channel access protocols; ii) radio is a broadcast medium and thus the action taken by a node has an effect on the actions taken by neighboring nodes and their outcome. Despite the complexity of the problem, there has been significant progress worth reporting on. The work accomplished so far has been either the analysis of specific examples of networks or an attempt to create models that would be useful in the design of general networks. The purpose of this paper is to survey the various modeling techniques that have been used for the performance analysis of packet radio networks, and to discuss the assumptions underlying these models, their scope of applicability, and some of the results obtained. This paper describes Extremely Opportunistic Routing (ExOR), a new unicast routing technique for multi-hop wireless networks. ExOR forwards each packet through a sequence of nodes, deferring the choice of each node in the sequence until after the previous node has transmitted the packet on its radio. ExOR then determines which node, of all the nodes that successfully received that transmission, is the node closest to the destination. That closest node transmits the packet. The result is that each hop moves the packet farther (or average) than the hops of the best possible pre-determined route.The ExOR design addresses the challenge of choosing a forwarding node after transmission using a distributed algorithm. First, when a node transmits a packet, it includes in the packet a simple schedule describing the priority order in which the potential receivers should forward the packet. The node computes the schedule based on shared measurements of inter-node delivery rates. ExOR then uses a distributed slotted MAC protocol for acknowledgements to ensure that the receivers agree who the highest priority receiver was.The efficacy of ExOR depends mainly on the rate at which the reception probability falls off with distance. Simulations based on measured radio characteristics [6] suggest that ExOR reduces the total number of transmissions by nearly a factor of two over the best possible pre-determined route. In this paper, we address the following question: given a specific placement of wireless nodes in physical space and a specific traffic workload, what is the maximum throughput that can be supported by the resulting network? Unlike previous work that has focused on computing asymptotic performance bounds under assumptions of homogeneity or randomness in the network topology and or workload, we work with any given network and workload specified as inputs.A key issue impacting performance is wireless interference between neighboring nodes. We model such interference using a conflict graph, and present methods for computing upper and lower bounds on the optimal throughput for the given network and workload. To compute these bounds, we assume that packet transmissions at the individual nodes can be finely controlled and carefully scheduled by an omniscient and omnipotent central entity, which is unrealistic. Nevertheless, using ns-2 simulations, we show that the routes derived from our analysis often yield noticeably better throughput than the default shortest path routes even in the presence of uncoordinated packet transmissions and MAC contention. This suggests that there is opportunity for achieving throughput gains by employing an interference-aware routing protocol. It is shown that the decision problem regarding the membership of a point in the capacity region of a packet radio network is nondeterministic polynomial time hard (NP hard). The capacity region is the set of all feasible origin-to-destination message rates where feasibility is defined as the existence of any set of rules for moving the data through the network so that the desired rates are satisfied. We consider a wireless broadcast station that transmits packets to multiple users. The packet requests for each user may overlap, and some users may already have certain packets. This presents a problem of broadcasting in the presence of side information, and is a generalization of the well-known (and unsolved) index coding problem of information theory. We represent the problem by a bipartite demand graph. Uncoded transmission is optimal if and only if this graph is acyclic. Next, we define a code-constrained capacity region that restricts attention to any prespecified set of coding actions. A dynamic max-weight algorithm that acts over variable length frames is developed. The algorithm allows for random packet arrivals and supports any traffic inside the code-constrained capacity region. A simple set of codes that exploit cycles in the demand graph are shown to be optimal for a class of broadcast relay problems. Topology Control (TC) is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption (which is essential to extend the network operational time) and radio interference (with a positive effect on the network traffic carrying capacity). The goal of this technique is to control the topology of the graph representing the communication links between network nodes with the purpose of maintaining some global graph property (e.g., connectivity), while reducing energy consumption and or interference that are strictly related to the nodes' transmitting range. In this article, we state several problems related to topology control in wireless ad hoc and sensor networks, and we survey state-of-the-art solutions which have been proposed to tackle them. We also outline several directions for further research which we hope will motivate researchers to undertake additional studies in this field. In CSMA CA-based, multi-hop, multi-rate wireless networks, spatial reuse can be increased by tuning the carrier-sensing threshold (Tcs) to reduce the carrier sense range (dcs). While reducing dcs enables more concurrent transmissions, the transmission quality suffers from the increased accumulative interference contributed by concurrent transmissions outside dcs. As a result, the data rate at which the transmission can sustain may decrease. How to balance the interplay of spatial reuse and transmission quality (and hence the sustainable data rate) so as to achieve high network capacity is thus an important issue. In this paper, we investigate this issue by extending Cali's model and devising an analytical model that characterizes the transmission activities as governed by IEEE 802.11 DCF in a single-channel, multi-rate, multi-hop wireless network. The systems throughput is derived as a function of Tcs, SINR, beta, and other PHY MAC systems parameters. We incorporate the effect of varying the degree of spatial reuse by tuning the Tcs. Based on the physical radio propagation model, we theoretically estimate the potential accumulated interference contributed by concurrent transmissions and the corresponding SINR. For a given SINR value, we then determine an appropriate data rate at which a transmission can sustain. To the best of our knowledge, this is perhaps the first effort that considers tuning of PHY characteristics (transmit power and data rates) and MAC parameters (contention backoff timer) jointly in an unified framework in order to optimize the overall network throughput. Analytical results indicate that the systems throughput is not a monotonically increasing decreasing function of Tcs, but instead exhibits transitional points where several possible choices of Tcs can be made. In addition, the network capacity can be further improved by choosing the backoff timer values appropriately. Spatial reuse TDMA is an access scheme for multi-hop radio networks. The idea is to increase capacity by letting several radio terminals use the same time slot when possible. A time slot can be shared when the radio units are geographically separated such that small interference is obtained. STDMA schedules can assign transmission rights to nodes or alternatively assign transmission rights to links, i.e. transmitter receiver pairs. Here we compare these two methods and determine which one is preferable. We show that only the connectivity of the network and the input traffic load of the network is needed in order to determine whether node or link assignment is preferable. Compared to single-hop networks such as WiFi, multihop infrastructure wireless mesh networks (WMNs) can potentially embrace the broadcast benefits of a wireless medium in a more flexible manner. Rather than being point-to-point, links in the WMNs may originate from a single node and reach more than one other node. Nodes located farther than a one-hop distance and overhearing such transmissions may opportunistically help relay packets for previous hops. This phenomenon is called opportunistic overhearing listening. With multiple radios, a node can also improve its capacity by transmitting over multiple radios simultaneously using orthogonal channels. Capitalizing on these potential advantages requires effective routing and efficient mapping of channels to radios (channel assignment (CA)). While efficient channel assignment can greatly reduce interference from nearby transmitters, effective routing can potentially relieve congestion on paths to the infrastructure. Routing, however, requires that only packets pertaining to a particular connection be routed on a predetermined route. Random network coding (RNC) breaks this constraint by allowing nodes to randomly mix packets overheard so far before forwarding. A relay node thus only needs to know how many packets, and not which packets, it should send. We mathematically formulate the joint problem of random network coding, channel assignment, and broadcast link scheduling, taking into account opportunistic overhearing, the interference constraints, the coding constraints, the number of orthogonal channels, the number of radios per node, and fairness among unicast connections. Based on this formulation, we develop a suboptimal, auction-based solution for overall network throughput optimization. Performance evaluation results show that our algorithm can effectively exploit multiple radios and channels and can cope with fairness issues arising from auctions. Our algorithm also shows promising gains over traditional routing solutions in which various channel assignment strategies are used. In this paper, we address the scheduling problem in wireless ad hoc networks by exploiting the computational advantage that comes when such scheduling problems can be represented by claw-free conflict graphs where we consider a wireless broadcast medium. It is possible to formulate a scheduling problem of network coded flows as finding maximum weighted independent set (MWIS) in the conflict graph of the network. Finding MWIS of a general graph is NP-hard leading to an NP-hard complexity of scheduling. In a claw-free conflict graph, MWIS can be found in polynomial time leading to a throughput-optimal scheduling. We show that the conflict graph of certain wireless ad hoc networks are claw-free. In order to obtain claw-free conflict graphs in general networks, we suggest introducing additional conflicts (edges) while keeping the decrease in MWIS size minimal. To this end, we introduce an iterative optimization problem to decide where to introduce edges and investigate its efficient implementation. Besides, we exemplify some physical modifications to manipulate the conflict graph of a network and also propose a mixed scheduling strategy for specific networks. We conclude that claw breaking method by adding extra edges can perform nearly optimal under the necessary assumptions. Many published algorithms used for scheduling transmissions in packet radio networks are based on finding maximal independent sets in an underlying graph. Such algorithms are developed under the assumptions of variations of the protocol interference model, which does not take the aggregated effect of interference into consideration. We provide a probabilistic analysis for the throughput performance of such graph based scheduling algorithms under the physical interference model. We show that in many scenarios a significant portion of transmissions scheduled based on the protocol interference model result in unacceptable signal-to-interference and noise ratio (SINR) at intended receivers. Our analytical as well as simulation results indicate that, counter intuitively, maximization of the cardinality of independent sets does not necessarily increase the throughput of a network. We introduce the truncated graph based scheduling algorithm (TGSA) that provides probabilistic guarantees for the throughput performance of the network. In this paper, we consider the transport capacity of ad hoc networks with a random flat topology under the present support of an infinite capacity infrastructure network. Such a network architecture allows ad hoc nodes to communicate with each other by purely using the remaining ad hoc nodes as their relays. In addition, ad hoc nodes can also utilize the existing infrastructure fully or partially by reaching any access point (or gateway) of the infrastructure network in a single or multi-hop fashion. Using the same tools as in [1], we show that the per source node capacity of T(W log(N)) can be achieved in a random network scenario with the following assumptions: (i) The number of ad hoc nodes per access point is bounded above, (ii) each wireless node, including the access points, is able to transmit at W bits sec using a fixed transmission range, and (iii) N ad hoc nodes, excluding the access points, constitute a connected topology graph. This is a significant improvement over the capacity of random ad hoc networks with no infrastructure support which is found as T(W vN log(N)) in [1]. Although better capacity figures may be obtained by complex network coding or exploiting mobility in the network, infrastructure approach provides a simpler mechanism that has more practical aspects. We also show that even when less stringent requirements are imposed on topology connectivity, a per source node capacity figure that is arbitrarily close to T(1) cannot be obtained. Nevertheless, under these weak conditions, we can further improve per node throughput significantly. In this paper, we consider CSMA policies for scheduling of multihop wireless networks with one-hop traffic. The main contribution of this paper is to propose Unlocking CSMA (U-CSMA) policy that enables to obtain high throughput with low (average) packet delay for large wireless networks. In particular, the delay under U-CSMA policy becomes order-optimal. For one-hop traffic, delay is defined to be order-optimal if it is O(1), i.e., it stays bounded, as the network-size increases to infinity. Using mean field theory techniques, we analytically show that for torus (grid-like) interference topologies with one-hop traffic, to achieve a network load of @math , the delay under U-CSMA policy becomes @math as the network-size increases, and hence, delay becomes order optimal. We conduct simulations for general random geometric interference topologies under U-CSMA policy combined with congestion control to maximize a network-wide utility. These simulations confirm that order optimality holds, and that we can use U-CSMA policy jointly with congestion control to operate close to the optimal utility with a low packet delay in arbitrarily large random geometric topologies. To the best of our knowledge, it is for the first time that a simple distributed scheduling policy is proposed that in addition to throughput utility-optimality exhibits delay order-optimality. Traditional wireless sensor networks (WSNs) working in the license-free spectrum suffer from uncontrolled interference as the license-free spectrum becomes increasingly crowded. Designing a WSN based on cognitive radio can be promising in the near future in order to provide data transmissions with quality of service requirements. In this paper we introduce a cognitive radio sensor network (CRSN) and analyze its performance for supporting real-time traffic. The network opportunistically accesses vacant channels in the licensed spectrum. When the current channel becomes unavailable, the devices can switch to another available channel. Two types of channel switchings are considered, in periodic switching (PS) the devices can switch to a new channel only at the beginning of each channel switching (CS) interval, while in triggered switching (TS) the devices can switch to a new channel as soon as the current channel is lost. We consider two types of real-time traffic, i) a burst of packets are generated periodically and the number of packets in each burst is random, and ii) packet arrivals follow a Poisson process. We derive the average packet transmission delay for each type of the traffic and channel switching mechanisms. Our results indicate that real-time traffic can be effectively supported in the CRSN with small average packet transmission delay. For the network using PS, packets with the Poisson arrivals experience longer average delay than the bursty arrivals; while for the network using TS, packets with the bursty arrivals experience longer average delay. We present a capacity-achieving coding scheme for unicast or multicast over lossy packet networks. In the scheme, intermediate nodes perform additional coding yet do not decode nor even wait for a block of packets before sending out coded packets. Rather, whenever they have a transmission opportunity, they send out coded packets formed from random linear combinations of previously received packets. All coding and decoding operations have polynomial complexity. We show that the scheme is capacity-achieving as long as packets received on a link arrive according to a process that has an average rate. Thus, packet losses on a link may exhibit correlation in time or with losses on other links. In the special case of Poisson traffic with i.i.d. losses, we give error exponents that quantify the rate of decay of the probability of error with coding delay. Our analysis of the scheme shows that it is not only capacity-achieving, but that the propagation of packets carrying "innovative" information follows the propagation of jobs through a queueing network, and therefore fluid flow models yield good approximations. We consider networks with both lossy point-to-point and broadcast links, allowing us to model both wireline and wireless packet networks. This paper considers the interaction between channel assignment and distributed scheduling in multi-channel multi-radio Wireless Mesh Networks (WMNs). Recently, a number of distributed scheduling algorithms for wireless networks have emerged. Due to their distributed operation, these algorithms can achieve only a fraction of the maximum possible throughput. As an alternative to increasing the throughput fraction by designing new algorithms, we present a novel approach that takes advantage of the inherent multi-radio capability of WMNs. We show that this capability can enable partitioning of the network into subnetworks in which simple distributed scheduling algorithms can achieve 100 throughput. The partitioning is based on the notion of Local Pooling. Using this notion, we characterize topologies in which 100 throughput can be achieved distributedly. These topologies are used in order to develop a number of centralized channel assignment algorithms that are based on a matroid intersection algorithm. These algorithms pre-partition a network in a manner that not only expands the capacity regions of the subnetworks but also allows distributed algorithms to achieve these capacity regions. We evaluate the performance of the algorithms via simulation and show that they significantly increase the distributedly achievable capacity region. We note that while the identified topologies are of general interference graphs, the partitioning algorithms are designed for networks with primary interference constraints. Recent advances in multi-radio multi-channel transmission technology have the potential of substantially improving the system capacity in multi-hop wireless networks. While previous work has primarily focused on the link level protocol design, in this paper we investigate the achievable performance gain, by jointly optimizing routing and scheduling in a multi-radio multichannel multi-hop network. We formulate the optimization under a deterministic model, and we seek to minimize overall system activation time in use to satisfy given end-to-end traffic demands subjected to the multi-access interference among neighboring transmissions and the radio interface constraint at each node. The exact solution to such an optimization problem is prohibitively complex due to the combinatorial complexity, particularly with the deployment of multi-radio and multi-channel. We develop a column generation based approach to solve this problem, which decomposes the original problem into sub-problems and solves them iteratively. Numerical results are given, and discussions as well as insights into the performance aspects for multi-radio multichannel deployment are provided.