Energy efficient random sleep-awake schedule design

This letter presents a simple model for determining energy efficient random sleep-awake schedules. Random sleepawake schedules are more appropriate for sensor networks, where the time of occurrence of an event being monitored, e.g., the detection of an intruder, is unknown a priori, and the coordination among nodes is costly. We model the random sleepawake schedule as a two state Markov process, and maximize the probability of the transmission of sensed data by a given deadline. Our results indicate that for a given duty cycle, the optimal policy is to have infrequent transitions between sleep and awake modes, if the average number of packets sent is greater than the mean number of slots the node is awake

Packet Arrival Analysis in Wireless Sensor Networks

Distributed sensor networks have been discussed for more than 30 years, but the vision of Wireless Sensor Networks (WSNs) has been brought into reality only by the rapid advancements in the areas of sensor design, information technologies, and wireless networks that have paved the way for the proliferation of WSNs. The unique characteristics of sensor networks introduce new challenges, amongst which prolonging the sensor lifetime is the most important. WSNs have seen a tremendous growth in various application areas including health care, environmental monitoring, security, and military purposes despite prominent performance and availability challenges. Clustering plays an important role in enhancement of the life span and scalability of the network, in such applications. Although researchers continue to address these grand challenges, the type of distributions for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. Modelling the behaviour of the networks becomes essential for estimating the performance metrics and further lead to decisions for improving the network performance, hence highlighting the importance of identifying the type of inter-arrival distributions at the cluster head. In this paper, we present extensive discussions on the assumptions of exponential distributions in WSNs, and present numerical results based on Q-Q plots for estimating the arrival distributions. The work is further extended to understand the impact of end-to-end delay and its effect on inter-arrival time distributions, based on the type of medium access control used in WSNs. Future work is also presented on the grounds that such comparisons based on simple eye checks are insufficient. Since in many cases such plots may lead to incorrect conclusions, demanding the necessity for validating the types of distributions. Statistical analysis is necessary to estimate and validate the empirical distributions of the arrivals in WSNs

Energy Efficient Sensor Scheduling with a Mobile Sink Node for the Target Tracking Application

Measurement losses adversely affect the performance of target tracking. The sensor network's life span depends on how efficiently the sensor nodes consume energy. In this paper, we focus on minimizing the total energy consumed by the sensor nodes whilst avoiding measurement losses. Since transmitting data over a long distance consumes a significant amount of energy, a mobile sink node collects the measurements and transmits them to the base station. We assume that the default transmission range of the activated sensor node is limited and it can be increased to maximum range only if the mobile sink node is out-side the default transmission range. Moreover, the active sensor node can be changed after a certain time period. The problem is to select an optimal sensor sequence which minimizes the total energy consumed by the sensor nodes. In this paper, we consider two different problems depend on the mobile sink node's path. First, we assume that the mobile sink node's position is known for the entire time horizon and use the dynamic programming technique to solve the problem. Second, the position of the sink node is varied over time according to a known Markov chain, and the problem is solved by stochastic dynamic programming. We also present sub-optimal methods to solve our problem. A numerical example is presented in order to discuss the proposed methods' performanc

An analytical model of MAC protocol dependant power consumption in multi-hop ad hoc wireless sensor networks

Power efficiency is the most constraining requirement for viable operation of battery-powered networked sensors. Conventionally, dynamic power management (DPM) is used to put sensor nodes into different states such as active, idle, and sleep, each consuming a certain level of power. Within the active state, communication operational states, such as receive and transmit consume different levels of nodal power. This thesis shows how DPM states and protocol operational states can be combined into a single stochastic model to finely evaluate the power consumption performance of a medium access control (MAC) protocol. The model is formulated as a semi-Markov decision process (SMDP) wherein the node\u27s states, sojourn times, and transition probabilities are controlled by a virtual node controller. The overall operation of a communication protocol is viewed as a randomized policy for the SMDP, and the long-run average cost per unit time measures the energy efficiency of the protocol

Does the assumption of exponential arrival distributions in wireless sensor networks hold?

Wireless Sensor Networks have seen a tremendous growth in various application areas despite prominent performance and availability challenges. One of the common configurations to prolong the lifetime and deal with the path loss phenomena having a multi-hop set-up with clusters and cluster heads to relay the information. Although researchers continue to address these challenges, the type of distribution for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. The general practice in published works is to compare an empirical exponential arrival distribution of wireless sensor networks with a theoretical exponential distribution in a Q-Q plot diagram. In this paper, we show that such comparisons based on simple eye checks are not sufficient since, in many cases, incorrect conclusions may be drawn from such plots. After estimating the Maximum Likelihood parameters of empirical distributions, we generate theoretical distributions based on the estimated parameters. By conducting Kolmogorov-Smirnov Test Statistics for each generated inter-arrival time distributions, we find out, if it is possible to represent the traffic into the cluster head by using theoretical distribution. Empirical exponential arrival distribution assumption of wireless sensor networks holds only for a few cases. There are both theoretically known such as Gamma, Log-normal and Mixed Log-Normal of arrival distributions and theoretically unknown such as non-Exponential and Mixed cases of arrival in wireless sensor networks. The work is further extended to understand the effect of delay on inter-arrival time distributions based on the type of medium access control used in wireless sensor networks

Determining the State of the Sensor Nodes Based on Fuzzy Theory in WSNs

The low-cost, limited-energy, and large-scale sensor nodes organize wireless sensor networks (WSNs). Sleep scheduling algorithms are introduced in these networks to reduce the energy consumption of the nodes in order to enhance the networklifetime. In this paper, a novel fuzzy method called Fuzzy Active Sleep (FAS) is proposed to activate the appropriate nodes of WSNs. It uses the selection probability of nodes based on their remaining energy and number of previous active state. Theproposed method focuses on a balanced sleep scheduling in order to belong the network lifetime. Simulation results show that the proposed method is more efficient and effective than the compared methods in terms of average network remaining energy, number of nodes still alive, number of active state, and network lifetime.

Does the assumption of exponential arrival distributions in wireless sensor networks hold?

Wireless Sensor Networks have seen a tremendous growth in various application areas despite prominent performance and availability challenges. One of the common configurations to prolong the lifetime and deal with the path loss phenomena having a multi-hop set-up with clusters and cluster heads to relay the information. Although researchers continue to address these challenges, the type of distribution for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. The general practice in published works is to compare an empirical exponential arrival distribution of wireless sensor networks with a theoretical exponential distribution in a Q-Q plot diagram. In this paper, we show that such comparisons based on simple eye checks are not sufficient since, in many cases, incorrect conclusions may be drawn from such plots. After estimating the Maximum Likelihood parameters of empirical distributions, we generate theoretical distributions based on the estimated parameters. By conducting Kolmogorov-Smirnov Test Statistics for each generated inter-arrival time distributions, we find out, if it is possible to represent the traffic into the cluster head by using theoretical distribution. Empirical exponential arrival distribution assumption of wireless sensor networks holds only for a few cases. There are both theoretically known such as Gamma, Log-normal and Mixed Log-Normal of arrival distributions and theoretically unknown such as non-Exponential and Mixed cases of arrival in wireless sensor networks. The work is further extended to understand the effect of delay on inter-arrival time distributions based on the type of medium access control used in wireless sensor networks

An Energy-Efficient Medium Access Control Protocol for Wireless Sensor Networks V-MAC

Wireless sensor networks (WSNs) are composed of hundreds of wireless sensors which collaborate to perform a common task. Because of the small size of wireless sensors, they have some serious limitations including very low computation capability and battery reserve. Such resource limitations require that WSN protocols to be extremely efficient. In this thesis, we focus on the Medium Access Control (MAC) layer in WSNs. We propose a MAC scheme, V-MAC, for WSNs that extends that lifetime of the network. We compare V-MAC with other MAC schemes. V-MAC uses a special mechanism to divide sensors in different groups and then all the members of a group go to sleep at the same time. V-MAC protects WSNs against denial of sleep and broadcast attacks. We present the V-MAC scheme in details and evaluate it with simulations. Our simulations show that V-MAC enjoys significantly higher throughput and network lifetime compared to other schemes

A Finite Queue Model Analysis of PMRC-based Wireless Sensor networks

In our previous work, a highly scalable and fault- tolerant network architecture, the Progressive Multi-hop Rotational Clustered (PMRC) structure, is proposed for constructing large-scale wireless sensor networks. Further, the overlapped scheme is proposed to solve the bottleneck problem in PMRC-based sensor networks. As buffer space is often scarce in sensor nodes, in this paper, we focus on studying the queuing performance of cluster heads in PMRC-based sensor networks. We develop a finite queuing model to analyze the queuing performance of cluster heads for both non-overlapped and overlapped PMRC-based sensor network. The average queue length and average queue delay of cluster head in different layers are derived. To validate the analysis results, simulations have been conducted with different loads for both non- overlapped and overlapped PMRC-based sensor networks. Simulation results match with the analysis results in general and confirm the advantage of selecting two cluster heads over selecting single cluster head in terms of the improved queuing performance