On the design of an energy-efficient low-latency integrated protocol for distributed mobile sensor networks

Self organizing, wireless sensors networks are an emergent and challenging technology that is attracting large attention in the sensing and monitoring community. Impressive progress has been done in recent years even if we need to assume that an optimal protocol for every kind of sensor network applications can not exist. As a result it is necessary to optimize the protocol for certain scenarios. In many applications for instance latency is a crucial factor in addition to energy consumption. MERLIN performs its best in such WSNs where there is the need to reduce the latency while ensuring that energy consumption is kept to a minimum. By means of that, the low latency characteristic of MERLIN can be used as a trade off to extend node lifetimes. The performance in terms of energy consumption and latency is optimized by acting on the slot length. MERLIN is designed specifically to integrate routing, MAC and localization protocols together. Furthermore it can support data queries which is a typical application for WSNs. The MERLIN protocol eliminates the necessity to have any explicit handshake mechanism among nodes. Furthermore, the reliability is improved using multiple path message propagation in combination with an overhearing mechanism. The protocol divides the network into subsets where nodes are grouped in time zones. As a result MERLIN also shows a good scalability by utilizing an appropriate scheduling mechanism in combination with a contention period

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Survey: energy efficient protocols using radio scheduling in wireless sensor network

An efficient energy management scheme is crucial factor for design and implementation of any sensor network. Almost all sensor networks are structured with numerous small sized, low cost sensor devices which are scattered over the large area. To improvise the network performance by high throughput with minimum energy consumption, an energy efficient radio scheduling MAC protocol is effective solution, since MAC layer has the capability to collaborate with distributed wireless networks. The present survey study provides relevant research work towards radio scheduling mechanism in the design of energy efficient wireless sensor networks (WSNs). The various radio scheduling protocols are exist in the literature, which has some limitations. Therefore, it is require developing a new energy efficient radio scheduling protocol to perform multi tasks with minimum energy consumption (e.g. data transmission). The most of research studies paying more attention towards to enhance the overall network lifetime with the aim of using energy efficient scheduling protocol. In that context, this survey study overviews the different categories of MAC based radio scheduling protocols and those protocols are measured by evaluating their data transmission capability, energy efficiency, and network performance. With the extensive analysis of existing works, many research challenges are stated. Also provides future directions for new WSN design at the end of this survey

Energy-efficient MAC protocol for wireless sensor networks

A Wireless Sensor Network (WSN) is a collection of tiny devices called sensor nodes which are deployed in an area to be monitored. Each node has one or more sensors with which they can measure the characteristics of their surroundings. In a typical WSN, the data gathered by each node is sent wirelessly through the network from one node to the next towards a central base station. Each node typically has a very limited energy supply. Therefore, in order for WSNs to have acceptable lifetimes, energy efficiency is a design goal that is of utmost importance and must be kept in mind at all levels of a WSN system. The main consumer of energy on a node is the wireless transceiver and therefore, the communications that occur between nodes should be carefully controlled so as not to waste energy. The Medium Access Control (MAC) protocol is directly in charge of managing the transceiver of a node. It determines when the transceiver is on/off and synchronizes the data exchanges among neighbouring nodes so as to prevent collisions etc., enabling useful communications to occur. The MAC protocol thus has a big impact on the overall energy efficiency of a node. Many WSN MAC protocols have been proposed in the literature but it was found that most were not optimized for the group of WSNs displaying very low volumes of traffic in the network. In low traffic WSNs, a major problem faced in the communications process is clock drift, which causes nodes to become unsynchronized. The MAC protocol must overcome this and other problems while expending as little energy as possible. Many useful WSN applications show low traffic characteristics and thus a new MAC protocol was developed which is aimed at this category of WSNs. The new protocol, Dynamic Preamble Sampling MAC (DPS-MAC) builds on the family of preamble sampling protocols which were found to be most suitable for low traffic WSNs. In contrast to the most energy efficient existing preamble sampling protocols, DPS-MAC does not cater for the worst case clock drift that can occur between two nodes. Rather, it dynamically learns the actual clock drift experienced between any two nodes and then adjusts its operation accordingly. By simulation it was shown that DPS-MAC requires less protocol overhead during the communication process and thus performs more energy efficiently than its predecessors under various network operating conditions. Furthermore, DPS-MAC is less prone to become overloaded or unstable in conditions of high traffic load and high contention levels respectively. These improvements cause the use of DPS-MAC to lead to longer node and network lifetimes, thus making low traffic WSNs more feasible.Dissertation (MEng)--University of Pretoria, 2008.Electrical, Electronic and Computer EngineeringMEngUnrestricte

On the Medium Access Control Protocols Suitable for Wireless Sensor Networks – A Survey

A MAC (Medium Access Control) protocol has direct impact on the energy efficiency and traffic characteristics of any Wireless Sensor Network (WSN). Due to the inherent differences in WSN’s requirements and application scenarios, different kinds of MAC protocols have so far been designed especially targeted to WSNs, though the primary mode of communications is wireless like any other wireless network. This is the subject topic of this survey work to analyze various aspects of the MAC protocols proposed for WSNs. To avoid collision and ensure reliability, before any data transmission between neighboring nodes in MAC layer, sensor nodes may need sampling channel and synchronizing. Based on these needs, we categorize the major MAC protocols into three classes, analyze each protocol’s relative advantages and disadvantages, and finally present a comparative summary which could give a snapshot of the state-of-the-art to guide other researchers find appropriate areas to work on. In spite of various existing survey works, we have tried to cover all necessary aspects with the latest advancements considering the major works in this area

Energy-Efficient Boarder Node Medium Access Control Protocol for Wireless Sensor Networks

This paper introduces the design, implementation, and performance analysis of the scalable and mobility-aware hybrid protocol named boarder node medium access control (BN-MAC) for wireless sensor networks (WSNs), which leverages the characteristics of scheduled and contention-based MAC protocols. Like contention-based MAC protocols, BN-MAC achieves high channel utilization, network adaptability under heavy traffic and mobility, and low latency and overhead. Like schedule-based MAC protocols, BN-MAC reduces idle listening time, emissions, and collision handling at low cost at one-hop neighbor nodes and achieves high channel utilization under heavy network loads. BN-MAC is particularly designed for region-wise WSNs. Each region is controlled by a boarder node (BN), which is of paramount importance. The BN coordinates with the remaining nodes within and beyond the region. Unlike other hybrid MAC protocols, BN-MAC incorporates three promising models that further reduce the energy consumption, idle listening time, overhearing, and congestion to improve the throughput and reduce the latency. One of the models used with BN-MAC is automatic active and sleep (AAS), which reduces the ideal listening time. When nodes finish their monitoring process, AAS lets them automatically go into the sleep state to avoid the idle listening state. Another model used in BN-MAC is the intelligent decision-making (IDM) model, which helps the nodes sense the nature of the environment. Based on the nature of the environment, the nodes decide whether to use the active or passive mode. This decision power of the nodes further reduces energy consumption because the nodes turn off the radio of the transceiver in the passive mode. The third model is the least-distance smart neighboring search (LDSNS), which determines the shortest efficient path to the one-hop neighbor and also provides cross-layering support to handle the mobility of the nodes. The BN-MAC also incorporates a semi-synchronous feature with a low duty cycle, which is advantageous for reducing the latency and energy consumption for several WSN application areas to improve the throughput. BN-MAC uses a unique window slot size to enhance the contention resolution issue for improved throughput. BN-MAC also prefers to communicate within a one-hop destination using Anycast, which maintains load balancing to maintain network reliability. BN-MAC is introduced with the goal of supporting four major application areas: monitoring and behavioral areas, controlling natural disasters, human-centric applications, and tracking mobility and static home automation devices from remote places. These application areas require a congestion-free mobility-supported MAC protocol to guarantee reliable data delivery. BN-MAC was evaluated using network simulator-2 (ns2) and compared with other hybrid MAC protocols, such as Zebra medium access control (Z-MAC), advertisement-based MAC (A-MAC), Speck-MAC, adaptive duty cycle SMAC (ADC-SMAC), and low-power real-time medium access control (LPR-MAC). The simulation results indicate that BN-MAC is a robust and energy-efficient protocol that outperforms other hybrid MAC protocols in the context of quality of service (QoS) parameters, such as energy consumption, latency, throughput, channel access time, successful delivery rate, coverage efficiency, and average duty cycle.https://doi.org/10.3390/s14030507

Fast Desynchronization For Decentralized Multichannel Medium Access Control

Distributed desynchronization algorithms are key to wireless sensor networks as they allow for medium access control in a decentralized manner. In this paper, we view desynchronization primitives as iterative methods that solve optimization problems. In particular, by formalizing a well established desynchronization algorithm as a gradient descent method, we establish novel upper bounds on the number of iterations required to reach convergence. Moreover, by using Nesterov's accelerated gradient method, we propose a novel desynchronization primitive that provides for faster convergence to the steady state. Importantly, we propose a novel algorithm that leads to decentralized time-synchronous multichannel TDMA coordination by formulating this task as an optimization problem. Our simulations and experiments on a densely-connected IEEE 802.15.4-based wireless sensor network demonstrate that our scheme provides for faster convergence to the steady state, robustness to hidden nodes, higher network throughput and comparable power dissipation with respect to the recently standardized IEEE 802.15.4e-2012 time-synchronized channel hopping (TSCH) scheme.Comment: to appear in IEEE Transactions on Communication

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