Unified clustering and communication protocol for wireless sensor networks

In this paper we present an energy-efficient cross layer protocol for providing application specific reservations in wireless senor networks called the “Unified Clustering and Communication Protocol ” (UCCP). Our modular cross layered framework satisfies three wireless sensor network requirements, namely, the QoS requirement of heterogeneous applications, energy aware clustering and data forwarding by relay sensor nodes. Our unified design approach is motivated by providing an integrated and viable solution for self organization and end-to-end communication is wireless sensor networks. Dynamic QoS based reservation guarantees are provided using a reservation-based TDMA approach. Our novel energy-efficient clustering approach employs a multi-objective optimization technique based on OR (operations research) practices. We adopt a simple hierarchy in which relay nodes forward data messages from cluster head to the sink, thus eliminating the overheads needed to maintain a routing protocol. Simulation results demonstrate that UCCP provides an energy-efficient and scalable solution to meet the application specific QoS demands in resource constrained sensor nodes. Index Terms — wireless sensor networks, unified communication, optimization, clustering and quality of service

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

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

Energy-delay region of low duty cycle wireless sensor networks for critical data collection

Session: Sensor networksThe Conference program's website is located at http://ita.ucsd.edu/workshop/14/talksWe investigate the trade-off between energy consumption and delay for critical data collection in low duty cycle wireless sensor networks, where a causality constraint exists for routing and link scheduling. We characterize the energy-delay region (E-D region) and formulate a combinatorial optimization problem to determine the link scheduling with the causality constraint. A new multiple-degree ordered (MDO) coloring method is proposed to solve this problem with near-optimal delay performance. The impacts of many system parameters on the ED region are evaluated by extensive simulation, providing an insightful frame of reference for design of critical data collection wireless sensor networks.postprin

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 Movement of Mobile Sink in Wireless Sensor Network to Conserve Energy

Energy is the major constraint in wireless sensor network. In wireless sensor network with static mobile collector (SNSMC),static nodes located near to sink consume more energy, since the nodes relay the data collected by sensor nodes far away from the sink. The battery drained in short time. This problem is resolved by the MMC-WSN method. While simplifying the routing process, proposing an energy-efficient routing technique based on cluster based method for mobile sink is preferred. First part ,the selection of cluster head (CH) in cluster based method made periodically according to their residual energy and in second part the mobile sink moves across the sensing field and directly collects data from cluster heads and returns to back to initial site in a specific sequence based on spanning graphs. The spanning graph includes the shortest search path for the MS. Finally, a tour-planning algorithm is used on the basis of the spanning graph. An energy efficient routing technique (EFR) in WSNs among obstacles uses the shortest route. In this way, the mobile sink retrieves all detected knowledge among a given time and sends to base station which reduces the packet delay and energy-consumption and WSNs