Ecosystems monitoring is essential to properly understand their development and the effects of events, both climatological and anthropological in nature. The amount of data used in these assessments is increasing at very high rates. This is due to increasing availability of sensing systems and the development of new techniques to analyze sensor data. The Enviro-Net Project encompasses several of such sensor system deployments across five countries in the Americas. These deployments use a few different ground-based sensor systems, installed at different heights monitoring the conditions in tropical dry forests over long periods of time. This paper presents our experience in deploying and maintaining these systems, retrieving and pre-processing the data, and describes the Web portal developed to help with data management, visualization and analysis.
Middleware software for automating control of deployments is also the focus of current research efforts, in form of architectures for integrating different network deployments @cite_46 , or Web-based interfaces for interaction with and control of wireless deployments @cite_28 . Our focus, on the other hand, is on managing the data products rather than controlling the equipment from within our system.
@cite_28 @cite_46
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Network deployments handle changing application, workload, and policy requirements via the deployment of specialized network appliances or "middleboxes". Today, however, middlebox platforms are expensive and closed systems, with little or no hooks for extensibility. Furthermore, they are acquired from independent vendors and deployed as standalone devices with little cohesiveness in how the ensemble of middleboxes is managed. As network requirements continue to grow in both scale and variety, this bottom-up approach puts middlebox deployments on a trajectory of growing device sprawl with corresponding escalation in capital and management costs. To address this challenge, we present CoMb, a new architecture for middlebox deployments that systematically explores opportunities for consolidation, both at the level of building individual middleboxes and in managing a network of middleboxes. This paper addresses key resource management and implementation challenges that arise in exploiting the benefits of consolidation in middlebox deployments. Using a prototype implementation in Click, we show that CoMb reduces the network provisioning cost 1.8-2.5× and reduces the load imbalance in a network by 2-25×. Management, allocation and scheduling of heterogeneous resources for complex distributed real-time applications is a challenging problem. Timing constraints of applications may be fulfilled by the proper use of real-time scheduling policies, admission control and enforcement of timing constraints. However, it is not easy to design basic infrastructure services that allow for easy access to the allocation of multiple heterogeneous resources in a distributed environment. In this paper, we present a middleware for providing distributed soft real-time applications with a uniform API for reserving heterogeneous resources with real-time scheduling capabilities in a distributed environment. The architecture relies on standard POSIX OS facilities, such as time management and standard TCP IP networking services, and it is designed around CORBA, in order to facilitate modularity, flexibility and portability of the applications using it. However, real-time scheduling is supported by proper extensions at the kernel-level, plugged within the framework by means of dedicated resource managers. Our current implementation on Linux supports the reservation of the CPU, disk and network bandwidth. However, additional resource managers supporting alternative real-time schedulers for these resources, as well as additional types of resources, may be easily added. We present experimental results gathered on both synthetic applications and a real multimedia video streaming case study, showing the advantages deriving from the use of the proposed middleware. Finally, overhead figures are reported, showing the sustainability of the approach for a wide class of complex, distributed, soft real-time applications. In this paper, experiences and best practices from using containerized software microservices for self-driving vehicles are shared. We applied the containerized software paradigm successfully to both the software development and deployment to turn our software architecture in the vehicles following the idea of microservices. Key enabling elements include onboarding of new developers, both researchers and students, traceable development and packaging, convenient and bare-bone deployment, and traceably archiving binary distributions of our quickly evolving software environment. In this paper, we share our experience from working one year with containerized development and deployment for our self-driving vehicles highlighting our reflections and application-specific shortcomings, our approach uses several components from the widely used Docker ecosystem, but the discussion in this paper generalizes these concepts. We conclude that the growingly complex automotive software systems in combination with their computational platforms should be rather understood as data centers on wheels to design both, (a) the software development and deployment processes, and (b) the software architecture in such a way to enable continuous integration, continuous deployment, and continuous experimentation. Interoperability and loose coupling requirements are pushing the next generation of distributed applications towards more decentralized and more dynamic interaction schemes, which the classic request response communication paradigm can hardly accommodate. Hence, sound foundations and mechanisms for the establishment of unanticipated peer-to-peer interactions across organizational boundaries are of significant importance to upcoming middleware platforms. The executable choreography framework (ECF) is a middleware-level framework that targets dynamic and decentralized service compositions. The ECF combines transparent context propagation with aspect-oriented software composition techniques to dynamically refine the default control and data flow of service invocations. The framework provides a ground for experimentation with dynamic and distributed workflows, and a base to assess their safety and applicability when deployed across organizational boundaries. In this work we present a middleware architecture for a mobile peer-to-peer content distribution system. Our architecture allows wireless content dissemination between mobile nodes without relying on infrastructure support. Contents are exchanged opportunistically when nodes are within communication range. Applications access the service of our platform through a publish subscribe interface and therefore do not have to deal with low-level opportunistic networking issues or matching and soliciting of contents. Our architecture consists of three key components. A content structure that facilitates dividing contents into logical topics and allows for efficient matching of content lookups and downloading under sporadic node connectivity. A solicitation protocol that allows nodes to solicit content meta-information in order to discover contents available at a neighboring node and to download content entries disjointedly from different nodes. An API that allows applications to access the system services through a publish subscribe interface. In this work we describe the design and implementation of our architecture. We also discuss potential applications and present evaluation results from profiling of our system. Conventionally, in order to control an application over a data network, a specific networked control or teleoperation algorithm to compensate network delay effects is usually required for controller design. Therefore, an existing controller has to be redesigned or replaced by a new controller system. This replacement process is usually costly, inconvenient, and time consuming. In this paper, a novel methodology to enable existing controllers for networked control and teleoperation by middleware is introduced. The proposed methodology uses middleware to modify the output of an existing controller based on a gain scheduling algorithm with respect to the current network traffic conditions. Since the existing controller can still be utilized, this approach could save much time and investment cost. Two examples of the middleware applied for networked control and teleoperation with IP network delays are given in these two companion papers. Part I of these two companion papers introduces the concept of the proposed middleware approach. Formulation, delay modeling, and optimal gain finding based on a cost function for a case study on DC motor speed control with a proportional-integral (PI) controller are also described. Simulation results of the PI controller shows that, with the existence of IP network delays, the middleware can effectively maintain the networked control system performance and stabilize the system. Part II of this paper will cover the use of the proposed middleware concept for a mobile robot teleoperation. This tutorial paper overviews recent developments in optimization-based approaches for resource allocation problems in wireless systems. We begin by overviewing important results in the area of opportunistic (channel-aware) scheduling for cellular (single-hop) networks, where easily implementable myopic policies are shown to optimize system performance. We then describe key lessons learned and the main obstacles in extending the work to general resource allocation problems for multihop wireless networks. Towards this end, we show that a clean-slate optimization-based approach to the multihop resource allocation problem naturally results in a "loosely coupled" cross-layer solution. That is, the algorithms obtained map to different layers [transport, network, and medium access control physical (MAC PHY)] of the protocol stack, and are coupled through a limited amount of information being passed back and forth. It turns out that the optimal scheduling component at the MAC layer is very complex, and thus needs simpler (potentially imperfect) distributed solutions. We demonstrate how to use imperfect scheduling in the cross-layer framework and describe recently developed distributed algorithms along these lines. We conclude by describing a set of open research problems In wireless networks there is strong coupling among the traditional layers of the architecture, and these interactions can not be ignored. One example is the interaction between routing in the network layer and access control in the MAC layer. Another one is the coupling between power control in the physical layer and the scheduling in the MAC layer. In this paper, we assume a TDMA-based wireless ad-hoc network; and provide a centralized algorithm of joint power control, scheduling, and routing. Simulation results are given to show the improvement of the network performance by using the joint algorithm. Energy efficiency is another very important topic for ad hoc networks, and is considered in our algorithm. Our simulation shows that there is a trade-off between the energy consumption and the network performance, such as throughput and delay. Algorithm for distributed implementation is also discussed. Large-scale, self-organizing wireless sensor and mesh network deployments are being driven by recent technological developments such as The Internet of Things (IoT), Smart Grids and Smart Environment applications. Efficient use of the limited energy resources of wireless sensor network (WSN) nodes is critically important to support these advances, and application of topology control methods will have a profound impact on energy efficiency and hence battery lifetime. In this survey, we focus on the energy efficiency issue and present a comprehensive study of topology control techniques for extending the lifetime of battery powered WSNs. First, we review the significant topology control algorithms to provide insights into how energy efficiency is achieved by design. Further, these algorithms are classified according to the energy conservation approach they adopt, and evaluated by the trade-offs they offer to aid designers in selecting a technique that best suits their applications. Since the concept of "network lifetime" is widely used for assessing the algorithms' performance, we highlight various definitions of the term and discuss their merits and drawbacks. Recently, there has been growing interest in algorithms for non-planar topologies such as deployments in underwater environments or multi-level buildings. For this reason, we also include a detailed discussion of topology control algorithms that work efficiently in three dimensions. Based on the outcomes of our review, we identify a number of open research issues for achieving energy efficiency through topology control. The paper validates the feasibility of automating the setting of common pilot power in a WCDMA radio network. The pilot automation improves operability of the network and it is implemented with a control software aiming for load and coverage balancing. The control applies measurements of base station total transmission power of neighboring cells and terminal reports of received pilot signal level to determine the pilot qualification. The pilot power of a cell is periodically updated with simple heuristic rules in order to improve the load and coverage balance. The approach was validated using a dynamic WCDMA system simulator with a deployment of macro and micro cells on a city region whose measured propagation characteristics were incorporated into the model. The results showed that the proposed control method balanced load and coverage and improved the air interface performance measured as a function of packet throughput. This paper discusses the design and implementation of a middleware guard for purposes of content filtering and information flow control in the Multiple Independent Levels of Security (MILS) architecture. The MILS initiative is a joint research effort between academia, industry, and government to develop and implement a high assurance real-time architecture for embedded systems. The MILS architecture incorporates a separation kernel with formal system security policies that are evaluatable, non-bypassable, tamper-proof, and always invoked. Vendor specific high-level applications are assumed to be untrustworthy components; information flow control needs to be performed by middleware entities external to the applications. In the MILS architecture, a MILS Message Router and guards are placed between communicating entities to act as message content filters and enforce information flow control. As the MILS architecture does not restrict the protocols that can be employed for communications between applications, a distinct guard is needed for filtering messages within each protocol. Incorporating protocol specific guards in MILS embedded systems aids in the formal certification of those systems or the high-assurance safety critical formally-proven applications. The guards enable formally-proven security policies that guarantee information flow control, data isolation, predictable process control, damage limitation, and resource availability. An example is provided using a multi-level secure file server that uses a GIOP guard for fine-grained access control. The inclusion of a GIOP guard reduces the complexity and the effort necessary for system certification. The deployment of cognitive radio networks enables efficient spectrum sharing and opportunistic spectrum access. It also presents new challenges to the classical problem of interference management in wireless networks. This paper develops an axiomatic framework for power allocation in cognitive radio networks based on four goals: QoS protection to primary users, opportunism to secondary users, admissibility to secondary users, and autonomous operation by individual users. Two additional goals, licensing and versatility, which are desirable rather than essential, are also presented. A general class of Duo Priority Class Power Control (DPCPC) policies that satisfy such goals is introduced. Through theoretical analysis and simulation, it is shown that a specific interference-aware power-control algorithm reaches such goals. Industrial Internet of things (IIoTs) relies on different devices working together, gathering and sharing data using multiple communication protocols. This heterogeneity becomes a hindrance in the development of architectures that can support applications operating independently of the underlying protocols. Therefore in this paper, we proposed a modular and scalable architecture based on lightweight virtualization. The modularity provided by the proposed architecture combined with lightweight virtualization orchestration supplied by Docker simplifies management and enables distributed deployments. Availability and fault-tolerance characteristics are ensured by distributing the application logic across different devices where a single microservice or even device failure can have no effect on system performance. The proposed architecture is instantiated and tested on a simple time-dependent use case. The obtained results validates that the proposed architecture can be used to deploy services on demand at different architecture layers. Intelligent collaborative environments, where heterogenous entities operate together in achieving common mission objectives have been increasingly adopted for monitoring and surveillance of interest areas and physical infrastructures. They can be assembled from multiple existing technologies ranging from wireless sensor networks (WSN), terrestrial remote operated vehicles (ROV) and unmanned aerial vehicles (UAV). In this context, we first introduce a multi-level system framework for multi-sensory robotic surveillance of critical infrastructure protection through communication, data acquisition and processing - MUROS. Leveraging a cognitive radio (CR) scheme is discussed as key point of the paper, arguing that by exploiting in an opportunistic fashion the time, frequency and spatial stream of the wireless environment, increased communication reliability can be achieved with positive impact on the availability and service level at each hierarchical level. The application of CR, given the heterogeneous nature of the application across multiple radio interfaces and protocols, stand outs as a novel and feasible research direction. We argument the advantages of this scheme within the constraints of a working scenario and define a simulation-based approach in order to validate our solution. In this paper, the problem of feedback and active user selection in multiple-input single-output (MISO) wireless systems such that the system’s stability region is as big as possible is examined. The focus is on a system in a Rayleigh fading environment where zero forcing precoding is used to serve all active users in every slot. Acquisition of the channel states is done via uplink training in time division duplexing mode by the active users. Clearly, only a subset of users can perform uplink training and the selection of this subset is a challenging and interesting problem especially in MISO systems. The stability regions of a baseline centralized scheme and two novel decentralized policies are examined analytically. In the decentralized schemes, the transmitter broadcasts periodically the queue state information and the users contend for the channel in a carrier sense multiple access-based manner with parameters based on the outdated queue state information and real-time channel state information. We show that, using infrequent signaling between the base station and the users, the decentralized policies outperform the centralized policy. In addition, a threshold-based user selection and training scheme for discrete-time contention is proposed. The results of this paper imply that, as far as stability is concerned, the users must be involved in the active user selection and feedback training decision. This should be leveraged in future communication systems. There's a difference between what we'd like our enterprise computing systems to be and what they really are. We like to envision them as orderly multitier arrangements comprising software buses, hubs, gateways, and adapters - all deployed at just the right places to maximize scale, load, application utility, and ultimately, business value. Unfortunately, we know that there's a wide gulf between this idealistic vision and reality. In practice, our enterprise computing systems typically are tangles of numerous technologies, protocols, and applications, often hastily hard-wired together with inflexible point-to-point connections. The whole point of middleware is to hide the diversity and complexity of the computing machinery underneath it. By adopting the abstractions that middleware provides, we're supposedly isolating our applications from the variety of ever-changing hardware platforms, operating systems, networks, protocols, and transports that make up our enterprise computing systems. We can use Web services to provide "middleware for middleware" abstraction layer for modern integration applications. Simulation has been the dominant research method- ology in wireless and sensor networking. When mobility is added, real-world experimentation is especially rare. However, it is becoming clear that simulation models do not sufficiently capture radio and sensor irregularity in a complex, real-world environment, especially indoors. Unfortunately, the high labor and equipment costs of truly mobile experimental infrastructure present high barriers to such experimentation. We describe our experience in creating a testbed to lower those barriers. We have extended the Emulab network testbed software to provide the first remotely-accessible mobile wireless and sensor testbed. Robots carry motes and single board computers through a fixed indoor field of sensor-equipped motes, all running the user's selected software. In real-time, interactively or driven by a script, remote users can position the robots, control all the computers and network interfaces, run arbitrary programs, and log data. Our mobile testbed provides simple path planning, a vision-based tracking system accurate to 1 cm, live maps, and webcams. Precise positioning and automation allow quick and painless evaluation of location and mobility effects on wireless protocols, location algorithms, and sensor-driven applications. The system is robust enough that it is deployed for public use. We present the design and implementation of our mobile testbed, evaluate key aspects of its performance, and describe a few experiments demonstrating its generality and power. The cloud radio access network (Cloud-RAN) has recently been proposed as one of the cost-effective and energy-efficient techniques for 5G wireless networks. By moving the signal processing functionality to a single baseband unit (BBU) pool, centralized signal processing and resource allocation are enabled in cloud-RAN, thereby providing the promise of improving the energy efficiency via effective network adaptation and interference management. In this paper, we propose a holistic sparse optimization framework to design green cloud-RAN by taking into consideration the power consumption of the fronthaul links, multicast services, as well as user admission control. Specifically, we first identify the sparsity structures in the solutions of both the network power minimization and user admission control problems, which call for adaptive remote radio head (RRH) selection and user admission. However, finding the optimal sparsity structures turns out to be NP-hard, with the coupled challenges of the @math -norm-based objective functions and the nonconvex quadratic QoS constraints due to multicast beamforming. In contrast to the previous works on convex but nonsmooth sparsity inducing approaches, e.g., the group sparse beamforming algorithm based on the mixed @math -norm relaxation, we adopt the nonconvex but smoothed @math -minimization ( @math @math $ -minimization problem from the SDR technique. We illustrate the effectiveness of the proposed algorithms with extensive simulations for network power minimization and user admission control in multicast cloud-RAN. Industrial applications aimed at real-time control and monitoring of cyber-physical systems pose significant challenges to the underlying communication networks in terms of determinism, low latency, and high reliability. The migration of these networks from wired to wireless could bring several benefits in terms of cost reduction and simplification of design, but currently available wireless techniques cannot cope with the stringent requirements of the most critical applications. In this paper, we consider the problem of designing a high-performance wireless network for industrial control, targeting at Gbps data rates and 10- @math s-level cycle time. To this aim, we start from analyzing the required performance and deployment scenarios, then we take a look at the most advanced standards and emerging trends that may be applicable. Building on this investigation, we outline the main directions for the development of a wireless high-performance system. In this paper, we design and test the performance of a distributed and adaptive resource management controller, which allows the optimal exploitation of cognitive radio and soft-input soft-output data fusion in vehicular access networks. The goal is to allow energy and computing-limited car smartphones to utilize the available vehicle-to-infrastructure (V2I) WiFi connections for performing traffic offloading toward local or remote clouds by opportunistically acceding to a spectral-limited wireless backbone built up by multiple roadside units (i.e., cloudlets). We cast the resource management problem into a suitable constrained stochastic network utility maximization problem and derive the optimal cognitive resource manager that dynamically allocates the access time windows at the serving roadside units (i.e., the access points), together with the access rates and traffic flows at the served vehicular clients (i.e., the secondary users of the wireless backbone). The developed controller provides hard reliability guarantees to the cloud service provider (i.e., the primary user of the wireless backbone) on a per-slot basis. Furthermore, it is able to acquire context information about the currently available bandwidth–energy resources to quickly adapt to the mobility-induced abrupt changes in the state of the vehicular network.