Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Distributed Clustering in Cognitive Radio Ad Hoc Networks Using Soft-Constraint Affinity Propagation

Absence of network infrastructure and heterogeneous spectrum availability in cognitive radio ad hoc networks (CRAHNs) necessitate the self-organization of cognitive radio users (CRs) for efficient spectrum coordination. The cluster-based structure is known to be effective in both guaranteeing system performance and reducing communication overhead in variable network environment. In this paper, we propose a distributed clustering algorithm based on soft-constraint affinity propagation message passing model (DCSCAP). Without dependence on predefined common control channel (CCC), DCSCAP relies on the distributed message passing among CRs through their available channels, making the algorithm applicable for large scale networks. Different from original soft-constraint affinity propagation algorithm, the maximal iterations of message passing is controlled to a relatively small number to accommodate to the dynamic environment of CRAHNs. Based on the accumulated evidence for clustering from the message passing process, clusters are formed with the objective of grouping the CRs with similar spectrum availability into smaller number of clusters while guaranteeing at least one CCC in each cluster. Extensive simulation results demonstrate the preference of DCSCAP compared with existing algorithms in both efficiency and robustness of the clusters

Overlapping Multi-hop Clustering for Wireless Sensor Networks

Clustering is a standard approach for achieving efficient and scalable performance in wireless sensor networks. Traditionally, clustering algorithms aim at generating a number of disjoint clusters that satisfy some criteria. In this paper, we formulate a novel clustering problem that aims at generating overlapping multi-hop clusters. Overlapping clusters are useful in many sensor network applications, including inter-cluster routing, node localization, and time synchronization protocols. We also propose a randomized, distributed multi-hop clustering algorithm (KOCA) for solving the overlapping clustering problem. KOCA aims at generating connected overlapping clusters that cover the entire sensor network with a specific average overlapping degree. Through analysis and simulation experiments we show how to select the different values of the parameters to achieve the clustering process objectives. Moreover, the results show that KOCA produces approximately equal-sized clusters, which allows distributing the load evenly over different clusters. In addition, KOCA is scalable; the clustering formation terminates in a constant time regardless of the network size

Vertex-linked infrastructure for ad hoc networks

An ad hoc network is composed of geographically dispersed nodes that may move arbitrarily and communicate with each other without the support of a stationary infrastructure. Compared with a wireless network with a stationary infrastructure, such as a cellular network, an ad hoc network is inherently less efficient. Therefore, a number of proposals have been made to develop a quasi-stationary infrastructure for ad hoc networks. However, the dynamic nature of ad hoc networks makes it very costly to maintain such an infrastructure. This article proposes a Vertex-Linked Infrastructure (VLI) for ad hoc networks. This novel approach uses an easily deployable, survivable, wired infrastructure as a backbone of the ad hoc network, thus realizing the advantages of an infrastructure in wireless communications, but without the overhead due to maintaining such an infrastructure.published_or_final_versio

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Hybrid routing and bridging strategies for large scale mobile ad hoc networks

Multi-hop packet radio networks (or mobile ad-hoc networks) are an ideal technology to establish instant communication infrastructure for military and civilian applications in which both hosts and routers are mobile. In this dissertation, a position-based/link-state hybrid, proactive routing protocol (Position-guided Sliding-window Routing - PSR) that provides for a flat, mobile ad-hoc routing architecture is described, analyzed and evaluated. PSR is based on the superposition of link-state and position-based routing, and it employs a simplified way of localizing routing overhead, without having to resort to complex, multiple-tier routing organization schemes. A set of geographic routing zones is defined for each node, where the purpose of the ith routing zone is to restrict propagation of position updates, advertising position differentials equal to the radius of the (i-i )th routing zone. Thus, the proposed protocol controls position-update overhead generation and propagation by making the overhead generation rate and propagation distance directly proportional to the amount of change in a node\u27s geographic position. An analytical model and framework is provided, in order to study the various design issues and trade-offs of PSR routing mechanism, discuss their impact on the protocol\u27s operation and effectiveness, and identify optimal values for critical design parameters, under different mobility scenarios. In addition an in-depth performance evaluation, via modeling and simulation, was performed in order to demonstrate PSR\u27s operational effectiveness in terms of scalability, mobility support, and efficiency. Furthermore, power and energy metrics, such as path fading and battery capacity considerations, are integrated into the routing decision (cost function) in order to improve PSR\u27s power efficiency and network lifetime. It is demonstrated that the proposed routing protocol is ideal for deployment and implementation especially in large scale mobile ad hoc networks. Wireless local area networks (WLAN) are being deployed widely to support networking needs of both consumer and enterprise applications, and IEEE 802.11 specification is becoming the de facto standard for deploying WLAN. However IEEE 802.11 specifications allow only one hop communication between nodes. A layer-2 bridging solution is proposed in this dissertation, to increase the range of 802.11 base stations using ad hoc networking, and therefore solve the hotspot communication problem, where a large number of mobile users require Internet access through an access point. In the proposed framework nodes are divided into levels based on their distance (hops) from the access point. A layer-2 bridging tree is built based on the level concept, and a node in certain level only forwards packets to nodes in its neighboring level. The specific mechanisms for the forwarding tree establishment as well as for the data propagation are also introduced and discussed. An analytical model is also presented in order to analyze the saturation throughput of the proposed mechanism, while its applicability and effectiveness is evaluated via modeling and simulation. The corresponding numerical results demonstrate and confirm the significant area coverage extension that can be achieved by the solution, when compared with the conventional 802.1 lb scheme. Finally, for implementation purposes, a hierarchical network structure paradigm based on the combination of these two protocols and models is introduced