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

EETA: An Energy Efficient Transmission Alignment for Wireless Sensor Network Applications

Energy conserving MAC protocols performing adaptive duty-cycling mechanism have been widely studied to improve the energy efficiency in Wireless Sensor Networks (WSNs). In particular, several asynchronous Low Power Listening (LPL) MAC protocols such as B-MAC, X-MAC and ContikiMAC transmit a long preamble or consecutive data packets for an efficient rendezvous between senders and receivers. However, the rendezvous results in the challenging problem of unnecessary channel utilization since the senders occupy a large portion of the medium. Furthermore, when a traffic generation time overlaps with other neighbouring nodes, they frequently encounter spatially-correlated contention incurring excessive channel contention. In this paper, we propose a novel traffic distribution scheme called an Energy Efficient Transmission Alignment (EETA), that shifts a traffic generation time of the application layer. By using a MAC layer feedback including contention information, the cross-layer framework determines whether the node delays its transmission or not. EETA is robust from the heavy contending environment due to its traffic distribution feature. We evaluate the performance of EETA through diverse experiments on the TelosB platform. The results show that EETA improves the overall energy efficiency by up to 35%, and reduces the latency by up to 48% compared to the existing scheme

Congestion Avoidance Energy Efficient MAC Protocol for Wireless Sensor Networks

Wireless Sensor Network (WSNs) are generally energy-constrained and resource-constrained. When multiple simultaneous events occur in densely deployed WSNs, nodes near the base station can become congested, decreasing the network performance. Additionally, multiple nodes may sense an event leading to spatially-correlated contention, further increasing congestion. In order to mitigate the effects of congestion near the base station, an energy-efficient Media Access Control (MAC) protocol that can handle multiple simultaneous events and spatially-correlated contention is needed. Energy efficiency is important and can be achieved using duty cycles but they could degrade the network performance in terms of latency. Existing protocols either provide support for congestion near the base station or for managing spatially-correlated contention. To provide energy-efficiency while maintaining the networks performance under higher traffic load, we propose an energy-efficient congestion-aware MAC protocol. This protocol provides support for congestion near the base station and spatially-correlated contention by employing a traffic shaping approach to manage the arrival times of packets to the layers close to the base station. We implemented our protocol using the ns-2 simulator for evaluating its performance. Results show that our protocol has an improvement in the number of packets received at the base station while consuming less energy

Dynamic Transmission Scheduling for Contention Mitigation in Wireless Sensor Networks

Wireless sensor networks (WSNs) heavily rely on a dense deployment of sensor nodes in order to ease deployment, increase fault-tolerance and network coverage, so that events do not go undetected. A dense deployment however results in several sensor nodes close to each other detecting and transmitting event reports at almost the same time, resulting in severe contention for channel access. Channel contention is a serious problem in WSNs resulting in collisions, re-transmissions, energy depletion, and ultimately loss of event reports. TDMA-based protocols prevent contention, but require tight synchronization and may lead to severe wastage of bandwidth especially in event-based applications where the traffic is bursty in nature. Other approaches that handle spatially correlated contention are fairly complex and contradict the reason for dense deployment, by selecting only a subset of nodes that generate and transmit event reports, affecting the fault-tolerance and confidence of event detection. Motivated by the challenge to reduce contention and improve performance, we propose a protocol that dynamically schedules transmissions in the network. The protocol exploits the broadcast nature of a wireless medium, which allows nodes to overhear transmissions of neighboring nodes and establish a cooperative transmission schedule dynamically, without the need for synchronization or explicit message exchange. To further mitigate contention, we propose a heuristic to reduce the number of active forwarder nodes in the network, by increasing the overlap of forwarder nodes used while routing packets. This forwarding mechanism can isolate the areas prone to interference, within which the dynamic transmission scheduling mechanism works better to mitigate contention. We evaluate the performance of our protocol using the NS2 simulator. Results show that our protocol significantly reduces collisions and re-transmissions, thereby improving the performance of the network

Congestion Mitigation by Traffic Dispersion in Wireless Sensor Networks

Wireless sensor networks (WSNs) are event-based systems that rely on the collective effort of several sensor nodes. When all nodes in an area sense an event and transmit that data, it causes sudden traffic bursts, which are spatially-correlated and lead to network congestion. Congestion can cause an increase in the amount of data loss, energy consumption, delay data transmission, and hinder network performance. To improve performance of event-driven applications, there arises a need for protocols that can reduce congestion and energy consumption. Existing protocols for sensing multiple events either handle congestion control or spatially-correlated contention, but not both, which can degrade network performance in terms of packet delivery ratio, latency, and energy consumption. Motivated primarily by the challenge to improve the performance of event-driven applications, we propose an energy efficient protocol to mitigate congestion that improves data delivery and reduces latency. This protocol mitigates congestion by dispersing network traffic using a forwarder selection mechanism that forces event reports from different nodes to disperse along different paths to the base station. Our protocol also reduces spatially-related contention by partitioning the sensors into different groups. All the sensors in a particular group cover the region of interest together, and these groups are scheduled in such that only one group is active to transmit the data at any given time. We implemented our protocol using the NS2 simulator for evaluating its performance. Results show that our protocol has significant improvement in the packet-delivery ratio, latency, and energy savings

Performance Analysis of a Compression Scheme for Highly Dense Cluster-Based Wireless Sensor Network

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