Many-to-One Communication Protocol for Wireless Sensor Networks

This paper proposes a novel communication protocol, called Many-to-One Sensors-to-Sink (MOSS), tailored to wireless sensor networks (WSNs). It exploits the unique sensors-to-sink traffic pattern to realize low-overhead medium access and low- latency sensors-to-sink routing paths. In conventional schedule-based MAC protocols such as S-MAC, sensor nodes in the proximity of the event generate reports simultaneously, causing unreliable and unpredictable performance during a brief but critical period of time when an event of interest occurs. MOSS is based on time division multiple access (TDMA) that avoids energy waste due to collisions, idle listening and overhearing and avoids unreliable behavior mentioned above. A small test-bed consisting of 12 TelosB motes as well as extensive simulation study based on ns-2 have shown that MOSS reduces the sensor-to-sink latency by as much as 50.5% while consuming only 12.8 ∼ 19.2% of energy compared to conventional TDMA algorithm

Joint duty cycle Scheduling, resource Allocation and multi-constrained QoS Routing algorithm

International audienceWireless mesh sensor networks (WMSNs) have recently gained a lot of interest due to their communication capability to support various applications with different Quality of Service (QoS) requirements. The most challenging issue is providing a tradeoff between the resource efficiency and the multiconstrained QoS support. For this purpose, we propose a cross-layer algorithm JSAR (Joint duty cycle Scheduling, resource Allocation and multi-constrained QoS Routing algorithm) for WMSNs on based multi-channel multi-time slot MAC. To our best knowledge, JSAR is the first algorithm which simultaneously combines, a duty cycle scheduling scheme for energy saving, a resource allocation scheme for efficient use of frequency channels and time slots, and an heuristic for multi-constrained routing protocol. The performance of JSAR has been evaluated, showing that it is suitable for on-line implementation

Enhanced delay-aware and reliable routing protocol for wireless sensor network

Wireless Sensor Networks (WSN) are distributed low-rate data networks, consist of small sensing nodes equipped with memory, processors and short range wireless communication. The performance of WSN is always measured by the Quality of Service (QoS) parameters that are time delay, reliability and throughput. These networks are dynamic in nature and affect the QoS parameters, especially when real time data delivery is needed. Additionally, in achieving end-to-end delay and reliability, link failures are the major causes that have not been given much attention. So, there is a demanding need of an efficient routing protocol to be developed in order to minimize the delay and provide on time delivery of data in real time WSN applications. An efficient Delay-Aware Path Selection Algorithm (DAPSA) is proposed to minimize the access end-to-end delay based on hop count, link quality and residual energy metrics considering the on time packets delivery. Furthermore, an Intelligent Service Classifier Queuing Model (ISCQM) is proposed to distinguish the real time and non-real time traffic by applying service discriminating theory to ensure delivery of real time data with acceptable delay. Moreover, an Efficient Data Delivery and Recovery Scheme (EDDRS) is proposed to achieve improved packet delivery ratio and control link failures in transmission. This will then improve the overall throughput. Based on the above mentioned approaches, an Enhanced Delay-Aware and Reliable Routing Protocol (EDARRP) is developed. Simulation experiments have been performed using NS2 simulator and multiple scenarios are considered in order to examine the performance parameters. The results are compared with the state-of-the-art routing protocols Stateless Protocol for Real-Time Communication (SPEED) and Distributed Adaptive Cooperative Routing Protocol (DACR) and found that on average the proposed protocol has improved the performance in terms of end-to-end delay (30.10%), packet delivery ratio (9.26%) and throughput (5.42%). The proposed EDARRP protocol has improved the performance of WSN

Minimum Latency Joint Scheduling and Routing in Wireless Sensor Networks

Wireless sensor networks are expected to be used in a wide range of applications from environment monitoring to event detection. The key challenge is to provide energy efficient communication; however, latency remains an important concern for many applications that require fast response. In this paper, we address the important problem of minimizing average communication latency for the active flows while providing energy-efficiency in wireless sensor networks. As the flows in some wireless sensor network can be long-lived and predictable, it is possible to design schedules for sensor nodes so that nodes can wake up only when it is necessary and asleep during other times. Clearly, the routing layer decision is closely coupled to the wakeup/sleep schedule of the sensor nodes. We formulate a joint scheduling and routing problem with the objective of finding the schedules and routes for current active flows with minimum average latency. By constructing a novel delay graph, the problem can be solved optimally by employing the M node-disjoint paths algorithm under FDMA channel model. We further extend the algorithm to handle dynamic traffic changes and topology changes in wireless sensor networks. We also propose a heuristic solution for the minimum latency joint scheduling and routing problem under single channel interference. Numerical results show the latency can reduced 15 % under stationary scenario and 50 % under dynamic traffic or topology changes. 1 I

Low Duty-Cycled Wireless Sensor Networks: Connectivity and Opportunistic Routing

This thesis addresses a number of performance and design issues that arise in a low duty-cycled wireless sensor network. The advances in sensing technology, miniaturization and wireless communication have led to a large number of emerging applications using networked wireless sensors. One of the most critical design goals is the longevity of the system. A widely accepted and commonly used method of energy conservation is duty cycling -- sensor nodes are periodically put to sleep mode to conserve energy. While effective in prolonging the system lifetime, duty-cycling disrupts communication and sensing capabilities as sensors alternate between sleep and wake modes. This not only affects network coverage and connectivity, but also causes delay in message delivery. A central theme of this thesis is to understand the energy-performance trade-off and design good networking algorithms that work well with low duty-cycled sensors. Our work thus centers on how the performance degradation caused by duty-cycling may be mitigated. The first method is to add redundancy to the deployment: the more sensors we deploy, the more we can reduce the duty cycle of individual sensors while maintaining the system level performance. In this context we investigate the fundamental relationship between the amount of redundancy required vs. the achievable reduction in duty cycle for a fixed performance criterion. We examine this relationship in the case of asymptotic network connectivity. A second method is to design good algorithms that effectively deal with temporal loss of connectivity. Within this context, we first develop a routing scheme using an optimal stochastic (also referred to as opportunistic) routing framework, designed to work in the presence of duty-cycling as well as unreliable wireless channels. We then examine how the routing delay of this type of algorithms scales compared to conventional (non-opportunistic) routing algorithms in a limiting regime where the network becomes dense. Lastly, for any routing algorithm to work properly there needs to be an efficient broadcast mechanism that discovers and disseminates topology information. In this context we develop an analysis-emulation hybrid model that combines analytical models with elements of numerical simulation to obtain the desired modeling accuracy and computational efficiency.Ph.D.Electrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/61569/1/kimds_1.pd