Metaheuristics Techniques for Cluster Head Selection in WSN: A Survey

In recent years, Wireless sensor communication is growing expeditiously on the capability to gather information, communicate and transmit data effectively. Clustering is the main objective of improving the network lifespan in Wireless sensor network. It includes selecting the cluster head for each cluster in addition to grouping the nodes into clusters. The cluster head gathers data from the normal nodes in the cluster, and the gathered information is then transmitted to the base station. However, there are many reasons in effect opposing unsteady cluster head selection and dead nodes. The technique for selecting a cluster head takes into factors to consider including residual energy, neighbors’ nodes, and the distance between the base station to the regular nodes. In this study, we thoroughly investigated by number of methods of selecting a cluster head and constructing a cluster. Additionally, a quick performance assessment of the techniques' performance is given together with the methods' criteria, advantages, and future directions

Online Distributed Sensor Selection

A key problem in sensor networks is to decide which sensors to query when, in order to obtain the most useful information (e.g., for performing accurate prediction), subject to constraints (e.g., on power and bandwidth). In many applications the utility function is not known a priori, must be learned from data, and can even change over time. Furthermore for large sensor networks solving a centralized optimization problem to select sensors is not feasible, and thus we seek a fully distributed solution. In this paper, we present Distributed Online Greedy (DOG), an efficient, distributed algorithm for repeatedly selecting sensors online, only receiving feedback about the utility of the selected sensors. We prove very strong theoretical no-regret guarantees that apply whenever the (unknown) utility function satisfies a natural diminishing returns property called submodularity. Our algorithm has extremely low communication requirements, and scales well to large sensor deployments. We extend DOG to allow observation-dependent sensor selection. We empirically demonstrate the effectiveness of our algorithm on several real-world sensing tasks

Exploiting the power of multiplicity: a holistic survey of network-layer multipath

The Internet is inherently a multipath network: For an underlying network with only a single path, connecting various nodes would have been debilitatingly fragile. Unfortunately, traditional Internet technologies have been designed around the restrictive assumption of a single working path between a source and a destination. The lack of native multipath support constrains network performance even as the underlying network is richly connected and has redundant multiple paths. Computer networks can exploit the power of multiplicity, through which a diverse collection of paths is resource pooled as a single resource, to unlock the inherent redundancy of the Internet. This opens up a new vista of opportunities, promising increased throughput (through concurrent usage of multiple paths) and increased reliability and fault tolerance (through the use of multiple paths in backup/redundant arrangements). There are many emerging trends in networking that signify that the Internet's future will be multipath, including the use of multipath technology in data center computing; the ready availability of multiple heterogeneous radio interfaces in wireless (such as Wi-Fi and cellular) in wireless devices; ubiquity of mobile devices that are multihomed with heterogeneous access networks; and the development and standardization of multipath transport protocols such as multipath TCP. The aim of this paper is to provide a comprehensive survey of the literature on network-layer multipath solutions. We will present a detailed investigation of two important design issues, namely, the control plane problem of how to compute and select the routes and the data plane problem of how to split the flow on the computed paths. The main contribution of this paper is a systematic articulation of the main design issues in network-layer multipath routing along with a broad-ranging survey of the vast literature on network-layer multipathing. We also highlight open issues and identify directions for future work

37th Annual WKU Student Research Conference

Western Kentucky University 38th Annual Student Research Conference program and student abstracts. Saturday, April 12, 2008, Carroll Knicely Conference Center, Bowling Green, Kentucky

Intelligent deployment strategies for passive underwater sensor networks

Passive underwater sensor networks are often used to monitor a general area of the ocean, a port or military installation, or to detect underwater vehicles near a high value unit at sea, such as a fuel ship or aircraft carrier. Deploying an underwater sensor network across a large area of interest (AOI), for military surveillance purposes, is a significant challenge due to the inherent difficulties posed by the underwater channel in terms of sensing and communications between sensors. Moreover, monetary constraints, arising from the high cost of these sensors and their deployment, limit the number of available sensors. As a result, sensor deployment must be done as efficiently as possible. The objective of this work is to develop a deployment strategy for passive underwater sensors in an area clearance scenario, where there is no apparent target for an adversary to gravitate towards, such as a ship or a port, while considering all factors pertinent to underwater sensor deployment. These factors include sensing range, communications range, monetary costs, link redundancy, range dependence, and probabilistic visitation. A complete treatment of the underwater sensor deployment problem is presented in this work from determining the purpose of the sensor field to physically deploying the sensors. Assuming a field designer is given a suboptimal number of sensors, they must be methodically allocated across an AOI. The Game Theory Field Design (GTFD) model, proposed in this work, is able to accomplish this task by evaluating the acoustic characteristics across the AOI and allocating sensors accordingly. Since GTFD considers only circular sensing coverage regions, an extension is proposed to consider irregularly shaped regions. Sensor deployment locations are planned using a proposed evolutionary approach, called the Underwater Sensor Deployment Evolutionary Algorithm, which utilizes two suitable network topologies, mesh and cluster. The effects of these topologies, and a sensor\u27s communications range, on the sensing capabilities of a sensor field, are also investigated. Lastly, the impact of deployment imprecision on the connectivity of an underwater sensor field, using a mesh topology, is analyzed, for cases where sensor locations after deployment do not exactly coincide with planned sensor locations

Game Theory Relaunched

The game is on. Do you know how to play? Game theory sets out to explore what can be said about making decisions which go beyond accepting the rules of a game. Since 1942, a well elaborated mathematical apparatus has been developed to do so; but there is more. During the last three decades game theoretic reasoning has popped up in many other fields as well - from engineering to biology and psychology. New simulation tools and network analysis have made game theory omnipresent these days. This book collects recent research papers in game theory, which come from diverse scientific communities all across the world; they combine many different fields like economics, politics, history, engineering, mathematics, physics, and psychology. All of them have as a common denominator some method of game theory. Enjoy

Advanced Resource Management Techniques for Next Generation Wireless Networks

The increasing penetration of mobile devices in everyday life is posing a broad range of research challenges to meet such a massive data demand. Mobile users seek connectivity "anywhere, at anytime". In addition, killer applications with multimedia contents, like video transmissions, require larger amounts of resources to cope with tight quality constraints. Spectrum scarcity and interference issues represent the key aspects of next generation wireless networks. Consequently, designing proper resource management solutions is critical. To this aim, we first propose a model to better assess the performance of Orthogonal Frequency-Division Multiple Access (OFDMA)-based simulated cellular networks. A link abstraction of the downlink data transmission can provide an accurate performance metric at a low computational cost. Our model combines Mutual Information-based multi-carrier compression metrics with Link-Level performance profiles, thus expressing the dependency of the transmitted data Block Error Rate (BLER) on the SINR values and on the modulation and coding scheme (MCS) being assigned. In addition, we aim at evaluating the impact of Jumboframes transmission in LTE networks, which are packets breaking the 1500-byte legacy value. A comparative evaluation is performed based on diverse network configuration criteria, thus highlighting specific limitations. In particular, we observed rapid buffer saturation under certain circumstances, due to the transmission of oversized packets with scarce radio resources. A novel cross-layer approach is proposed to prevent saturation, and thus tune the transmitted packet size with the instantaneous channel conditions, fed back through standard CQI-based procedures. Recent advances in wireless networking introduce the concept of resource sharing as one promising way to enhance the performance of radio communications. As the wireless spectrum is a scarce resource, and its usage is often found to be inefficient, it may be meaningful to design solutions where multiple operators join their efforts, so that wireless access takes place on shared, rather than proprietary to a single operator, frequency bands. In spite of the conceptual simplicity of this idea, the resulting mathematical analysis may be very complex, since it involves analytical representation of multiple wireless channels. Thus, we propose an evaluative tool for spectrum sharing techniques in OFDMA-based wireless networks, where multiple sharing policies can be easily integrated and, consequently, evaluated. On the other hand, relatively to contention-based broadband wireless access, we target an important issue in mobile ad hoc networks: the intrinsic inefficiency of the standard transmission control protocol (TCP), which presents degraded performance mainly due to mechanisms such as congestion control and avoidance. In fact, TCP was originally designed for wired networks, where packet losses indicate congestion. Conversely, channels in wireless networks might vary rapidly, thus most loss events are due to channel errors or link layer contention. We aim at designing a light-weight cross-layer framework which, differently from many other works in the literature, is based on the cognitive network paradigm. It includes an observation phase, i.e., a training set in which the network parameters are collected; a learning phase, in which the information to be used is extracted from the data; a planning phase, in which we define the strategies to trigger; an acting phase, which corresponds to dynamically applying such strategies during network simulations. The next generation mobile infrastructure frontier relies on the concept of heterogeneous networks. However, the existence of multiple types of access nodes poses new challenges such as more stringent interference constraints due to node densification and self-deployed access. Here, we propose methods that aim at extending femto cells coverage range by enabling idle User Equipments (UE) to serve as relays. This way, UEs otherwise connected to macro cells can be offloaded to femto cells through UE relays. A joint resource allocation and user association scheme based on the solutions of a convex optimization problem is proposed. Another challenging issue to be addressed in such scenarios is admission control, which is in charge of ensuring that, when a new resource reservation is accepted, previously connected users continue having their QoS guarantees honored. Thus, we consider different approaches to compute the aggregate projected capacity in OFDMA-based networks, and propose the E-Diophantine solution, whose mathematical foundation is provided along with the performance improvements to be expected, both in accuracy and computational terms