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

A Cross-Layer Design Approach to Enhance 802.15.4

The low-power communication in wireless sensor networks can be impacted by severe channel impairments. In this paper, to address this problem and achieve high network goodput, we propose that the medium access control protocol takes into consideration the error performance of the underlying wireless links. We combine a distributed back-off strategy regulated by the wireless link quality with Carrier Sense Multiple Access with Collision Avoidance. We integrate our cross-layer operational approach in the IEEE 802.15.4 standard, taking advantage of existing functionality and signaling to avoid network overhead and achieve simplicity in implementation. Our performance evaluation indicates that our scheme is more effective, achieving up to 69% higher goodput, and more efficient, delivering up to 154% more data bits per unit of energy consumed in the network, at the expense of an up to 18% degradation in fairness, compared to the basic 802.15.4

Real-Time Cross-Layer Routing Protocol for Ad Hoc Wireless Sensor Networks

Reliable and energy efficient routing is a critical issue in Wireless Sensor Networks (WSNs) deployments. Many approaches have been proposed for WSN routing, but sensor field implementations, compared to computer simulations and fully-controlled testbeds, tend to be lacking in the literature and not fully documented. Typically, WSNs provide the ability to gather information cheaply, accurately and reliably over both small and vast physical regions. Unlike other large data network forms, where the ultimate input/output interface is a human being, WSNs are about collecting data from unattended physical environments. Although WSNs are being studied on a global scale, the major current research is still focusing on simulations experiments. In particular for sensor networks, which have to deal with very stringent resource limitations and that are exposed to severe physical conditions, real experiments with real applications are essential. In addition, the effectiveness of simulation studies is severely limited in terms of the difficulty in modeling the complexities of the radio environment, power consumption on sensor devices, and the interactions between the physical, network and application layers. The routing problem in ad hoc WSNs is nontrivial issue because of sensor node failures due to restricted recourses. Thus, the routing protocols of WSNs encounter two conflicting issue: on the one hand, in order to optimise routes, frequent topology updates are required, while on the other hand, frequent topology updates result in imbalanced energy dissipation and higher message overhead. In the literature, such as in (Rahul et al., 2002), (Woo et al., 2003), (TinyOS, 2004), (Gnawali et al., 2009) and (Burri et al., 2007) several authors have presented routing algorithms for WSNs that consider purely one or two metrics at most in attempting to optimise routes while attempting to keep small message overhead and balanced energy dissipation. Recent studies on energy efficient routing in multihop WSNs have shown a great reliance on radio link quality in the path selection process. If sensor nodes along the routing path and closer to the base station advertise a high quality link to forwarding upstream packets, these sensor nodes will experience a faster depletion rate in their residual energy. This results in a topological routing hole or network partitioning as stated and resolved in and (Daabaj 2010). This chapter presents an empirical study on how to improve energy efficiency for reliable multihop communication by developing a real-time cross-layer lifetime-oriented routing protocol and integrating useful routing information from different layers to examine their joint benefit on the lifetime of individual sensor nodes and the entire sensor network. The proposed approach aims to balance the workload and energy usage among relay nodes to achieve balanced energy dissipation, thereby maximizing the functional network lifetime. The obtained experimental results are presented from prototype real-network experiments based on Crossbow’s sensor motes (Crossbow, 2010), i.e., Mica2 low-power wireless sensor platforms (Crossbow, 2010). The distributed real-time routing protocol which is proposed In this chapter aims to face the dynamics of the real world sensor networks and also to discover multiple paths between the base station and source sensor nodes. The proposed routing protocol is compared experimentally with a reliability-oriented collection-tree protocol, i.e., the TinyOS MintRoute protocol (Woo et al., 2003). The experimental results show that our proposed protocol has a higher node energy efficiency, lower control overhead, and fair average delay

An Energy-efficient Rate Adaptive Media Access Protocol (RA-MAC) for Long-lived Sensor Networks

We introduce an energy-efficient Rate Adaptive Media Access Control (RA-MAC) algorithm for long-lived Wireless Sensor Networks (WSNs). Previous research shows that the dynamic and lossy nature of wireless communications is one of the major challenges to reliable data delivery in WSNs. RA-MAC achieves high link reliability in such situations by dynamically trading off data rate for channel gain. The extra gain that can be achieved reduces the packet loss rate which contributes to reduced energy expenditure through a reduced numbers of retransmissions. We achieve this at the expense of raw bit rate which generally far exceeds the application’s link requirement. To minimize communication energy consumption, RA-MAC selects the optimal data rate based on the estimated link quality at each data rate and an analytical model of the energy consumption. Our model shows how the selected data rate depends on different channel conditions in order to minimize energy consumption. We have implemented RA-MAC in TinyOS for an off-the-shelf sensor platform (the TinyNode) on top of a state-of-the-art WSN Media Access Control Protocol, SCP-MAC, and evaluated its performance by comparing our implementation with the original SCP-MAC using both simulation and experiment

Real-time Power Aware Routing in Wireless Sensor Networks

Many mission-critical wireless sensor network applications must resolve the inherent conflict between the tight resource constraints on each sensor node, particularly in terms of energy, with the need to achieve desired quality of service such as end-to-end real-time performance. To address this challenge we propose the Real-time Power-Aware Routing (RPAR) protocol. RPAR achieves required communication delays at minimum energy cost by dynamically adapting the transmission power and routing decisions based on packet deadlines. RPAR integrates a geographic forwarding policy cognizant of deadlines, power, and link quality with new algorithms for on-demand power adaptation and efficient neighborhood discovery. Simulations based on a realistic radio model of MICA2 motes show that RPAR significantly reduces the number of deadline misses and energy consumption when compared to existing real-time and energy-efficient routing protocols and beacon based neighborhood management schemes

Modeling and Implementation of Wireless Sensor Networks for Logistics Applications

Logistics has experienced a long time of developments and improvements based on the advanced vehicle technologies, transportation systems, traffic network extension and logistics processes. In the last decades, the complexity has increased significantly and this has created complex logistics networks over multiple continents. Because of the close cooperation, these logistics networks are highly dependent on each other in sharing and processing the logistics information. Every customer has many suppliers and vice versa. The conventional centralized control continues but reaches some limitations such as the different distribution of suppliers, the complexity and flexibility of processing orders or the dynamics of the logistic objects. In order to overcome these disadvantages, the paradigm of autonomous logistics is proposed and promises a better technical solution for current logistics systems. In autonomous logistics, the decision making is shifted toward the logistic objects which are defined as material items (e.g., vehicles, containers) or immaterial items (e.g., customer orders) of a networked logistics system. These objects have the ability to interact with each other and make decisions according to their own objectives. In the technical aspect, with the rapid development of innovative sensor technology, namely Wireless Sensor Networks (WSNs), each element in the network can self-organize and interact with other elements for information transmission. The attachment of an electronic sensor element into a logistic object will create an autonomous environment in both the communication and the logistic domain. With this idea, the requirements of logistics can be fulfilled; for example, the monitoring data can be precise, comprehensive and timely. In addition, the goods flow management can be transferred to the information logistic object management, which is easier by the help of information technologies. However, in order to transmit information between these logistic objects, one requirement is that a routing protocol is necessary. The Opportunistic relative Distance-Enabled Uni-cast Routing (ODEUR ) protocol which is proposed and investigated in this thesis shows that it can be used in autonomous environments like autonomous logistics. Moreover, the support of mobility, multiple sinks and auto-connection in this protocol enhances the dynamics of logistic objects. With a general model which covers a range from low-level issues to high-level protocols, many services such as real time monitoring of environmental conditions, context-aware applications and localization make the logistic objects (embedded with sensor equipment) more advanced in information communication and data processing. The distributed management service in each sensor node allows the flexible configuration of logistic items at any time during the transportation. All of these integrated features introduce a new technical solution for smart logistic items and intelligent transportation systems. In parallel, a management system, WSN data Collection and Management System (WiSeCoMaSys), is designed to interact with the deployed Wireless Sensor Networks. This tool allows the user to easily manipulate the sensor networks remotely. With its rich set of features such as real time data monitoring, data analysis and visualization, per-node management, and alerts, this tool helps both developers and users in the design and deployment of a sensor network. In addition, an analytical model is developed for comparison with the results from simulations and experiments. Focusing on the use of probability theory to model the network links, this model considers several important factors such as packet reception rate and network traffic which are used in the simulation and experiment parts. Moreover, the comparison between simulation, experiment and analytical results is also carried out to estimate the accuracy of the design and make several improvements of the simulation accuracy. Finally, all of the above parts are integrated in one unique system. This system is verified by both simulations in logistic scenarios (e.g., harbors, warehouses and containers) and experiments. The results show that the proposed model and protocol have a good packet delivery rate, little memory requirements and low delay. Accordingly, this system design is practical and applicable in logistics

Channel acquisition and routing system for real-time cognitive radio sensor networks

The need for efficient spectrum utilization and routing has ignited interest in the Cognitive Radio Sensor Network (CRSN) paradigm among researchers. CRSN ensures efficient spectrum utilization for wireless sensor network. However, the main challenge faced by CRSN users have to deal with is the issue of service quality in terms of interference when using channels and degradation in multi-hop communication. This thesis proposes to overcome the interference due to contention and routing issues through the design of an efficient Channel Acquisition and Reliable routing System (CARS). CARS is designed to reduce carrier sense multiple access contention and enhance routing in CRSNs. CARS comprises of Lightweight Distributed Geographical (LDG), and Reliable Opportunists Routing (ROR) modules. LDG is a medium access control centric; cross-layer designed protocol to acquire a common control channel for signalling to determine the data channel. ROR is a network-centric cross-layer designed protocol to decide on a path for routing data packets. The result shows that LDG significantly reduces the overhead of media access contention and energy cost by at an average of 70% and 80% respectively compared to other approaches that use common control channel acquisition like Efficient Recovery Control Channel (ERCC) protocol. In addition, LDG achieves a 16.3% boost in the time to rendezvous on the control channel above ERCC and a 36.9% boost above Coordinated Channel Hopping (CCH) protocol. On the other hand, the virtual clustering framework inspired by ROR has further improved network performance. The proposed ROR significantly increases packet received at the sink node by an average of over 20%, reduces end-to-end latency by an average of 37% and minimizes energy consumption by an average of 22% as compared to Spectrum-aware Clustering for Efficient Multimedia routing (SCEEM) protocol. In brief, the design of CARS which takes the intrinsic characteristics of CRSNs into consideration helps to significantly reduce the energy needed for securing a control channel and to guarantee that end-to-end, real-time conditions are preserved in terms of latency and media content. Thus, LDG and ROR are highly recommended for real-time data transmission such as multimedia data transfer in CRSN