Vyacheslav V. Zalyubovskiy

Energy-efficient Area Coverage by Sensors with Adjustable Ranges

In wireless sensor networks, density control is an important technique for prolonging a networks lifetime. To reduce the overall energy consumption, it is desirable to minimize the overlapping sensing area of sensor nodes. In this paper, we study the problem of energy-efficient area coverage by the regular placement of sensors with adjustable sensing and communication ranges. We suggest a more accurate method to estimate efficiency than those currently used for coverage by sensors with adjustable ranges, and propose new density control models that considerably improve coverage using sensors with two sensing ranges. Calculations and extensive simulation show that the new models outperform existing ones in terms of various performance metrics.

Level-based approach for minimum-transmission broadcast in duty-cycled wireless sensor networks

Broadcast is a fundamental activity in wireless sensor networks (WSNs) and many problems related to broadcast have been formulated and investigated in the literature. Among them, the minimum-transmission broadcast (MTB) problem, which aims to reduce broadcast redundancy, has been well studied in conventional wireless ad hoc networks, where network nodes are assumed to be active all the time. In this paper, we study the MTB problem in duty-cycled WSNs where sensor nodes operate under active/dormant cycle and propose a novel scheme to solve it efficiently. The proposed Level-Based Approximation Scheme first identifies the forwarding nodes and their corresponding receivers for all time slots; then constructs a broadcast backbone by connecting these forwarding nodes to the broadcast source. The backbone construction is accomplished by a two-stage traversal on all the forwarding nodes, which successfully exploits transmissions of each forwarding node to its receivers. We have also conducted extensive simulations to evaluate the performance of our proposed scheme. Simulation results indicate that our scheme significantly outperforms existing ones. The algorithm of finding covering nodes helps to reduce a number of transmissions.The concept of duty-transmission highlights the advantage of our scheme.Level-based traversal on covering nodes reduces a number of transmissions and the time complexity.Examining the impact of network density and duty cycle shows the advantage of our scheme.The trade-off between number of broadcast transmissions and broadcast delay is also disclosed.

Delay-minimized Energy-efficient Data Aggregation in Wireless Sensor Networks

Data aggregation is a fundamental problem in wireless sensor networks that has attracted great attention in recent years. To design a data aggregation scheme, delay and energy efficiencies are two crucial issues that require much consideration. In this paper, we propose a distributed, energy-efficient algorithm for collecting data from all sensor nodes with minimum latency called Delay-minimized Energy-efficient Data Aggregation algorithm (DEDA). The DEDA algorithm minimizes data aggregation latency by building a delay-efficient network structure. At the same time, it also considers the distances between network nodes for saving sensor transmission power and network energy. Energy consumption is also well-balanced between sensors to achieve an acceptable network lifetime. The simulation results show that the scheme could significantly decrease data aggregation delay and obtain a reasonable network lifetime compared with other approaches.

LABS: Latency aware broadcast scheduling in uncoordinated Duty-Cycled Wireless Sensor Networks

Abstract Broadcast is a fundamental operation in Wireless Sensor Networks (WSNs) and plays an important role in a communication protocol design. In duty-cycled scenarios, a sensor node can receive a message only in its active time slot, which makes it more difficult to design collision-free scheduling for broadcast operations. Recent studies in this area have focused on minimizing broadcast latency and guaranteeing that all nodes receive a broadcast message. This paper investigates the problem of Minimum Latency Broadcast Scheduling in Duty-Cycled (MLBSDC) WSNs. By using special geometric properties of independent sets of a broadcast tree, we reduce the number of transmissions, consequently reducing the possibility of collision. Allowing multiple transmissions in one working period, our proposed Latency Aware Broadcast Scheduling (LABS) scheme provides a latency-efficient broadcast schedule. Theoretical analysis proves that the scheme has the same approximation ratio and complexity as the previous best algorithm for the MLBSDC problem. Moreover, simulation shows that the new scheme achieves up to 34%, 37%, and 21% performance improvement over previous schemes, in terms of latency, number of transmissions, and energy consumption, respectively.

Collision-tolerant broadcast scheduling in duty-cycled wireless sensor networks

The minimum-latency broadcast problem in duty-cycled wireless sensor networks has received significant attention over the last few years. A common approach for the problem is to assign collision-free transmitting times to forwarding nodes for disseminating a message from one source node to all other nodes according to their given duty-cycle schedules and transmission ranges. However, preventing collision for all transmissions may increase latency in the broadcast schedules. This paper proposes a novel strategy of Collision-Tolerant Scheduling (CTS) that offers an opportunity to reduce broadcast latency by allowing collisions at non-critical nodes to speed up the broadcast process for critical ones. The completion of broadcast scheduling, i.e. all nodes receive a broadcast message, is ensured by additionally transmitting the message to non-critical nodes experiencing collision. We employ the scheduling strategy in two proposed broadcast schemes: Degree-based CTS (DCTS) and MIS-based CTS (MCTS), which select forwarding nodes based on the node degree and maximal independent set information, respectively. The results of both theoretical analysis and simulation reveal the remarkable advantages of CTS in minimizing broadcast latency in duty-cycled WSNs. DCTS and MCTS guarantee approximation ratios of (1)T and 12T in terms of broadcast latency, where and T denote the maximum node degree and the number of time slots in a working period, respectively. The two schemes reduce to at least 94 percent of the broadcast latency compared with existing schemes, while slightly increasing the number of transmissions due to the additional transmissions. Thanks to the latency reduction, the proposed schemes require 93 percent less energy than existing ones. A novel scheduling strategy for broadcast latency minimization in duty-cycled WSNs.Allowing collisions at non-critical nodes to speed up the broadcast process.The completion of broadcast scheduling is ensured by additional transmissions.Achieving significant improvement in both theoretical and simulation results.

Towards broadcast redundancy minimization in duty-cycled wireless sensor networks

Summary Broadcast is an essential operation in wireless sensor networks. Because of the necessity of energy conservation, minimizing the number of transmissions is always a challenging issue in broadcasting scheme design. This paper studies the minimum-transmission broadcast problem in duty-cycled wireless sensor networks where each sensor operates under active/dormant cycles. To address the problem, our proposed scheme, Broadcast Redundancy Minimization Scheduling (BRMS), finds a set of forwarding nodes, which minimizes the number of broadcast transmissions. Then, it constructs a forest of sub-trees based on the relationship between each forwarding node and its corresponding receivers. A broadcast tree is constructed ultimately by connecting all sub-trees with a minimum number of connectors. Theoretical analysis shows that BRMS obtains a lower approximation ratio as well as time complexity compared with existing schemes. A set of extensive simulations is conducted to evaluate the performance of BRMS. The results reveal that BRMS outperforms others and its solution is close to the lower bound of the problem in terms of the total number of transmissions. Copyright

A Distributed Delay-Efficient Data Aggregation Scheduling for Duty-Cycled WSNs

With the growing interest in wireless sensor networks (WSNs), minimizing network delay and maximizing sensor (node) lifetime are important challenges. Since the sensor battery is one of the most precious resources in a WSN, efficient utilization of the energy to prolong the network lifetime has been the focus of much of the research on WSNs. For that reason, many previous research efforts have tried to achieve tradeoffs in terms of network delay and energy cost for such data aggregation tasks. Recently, duty-cycling technique, i.e., periodically switching ON and OFF communication and sensing capabilities, has been considered to significantly reduce the active time of sensor nodes and thus extend network lifetime. However, this technique causes challenges for data aggregation. In this paper, we present a distributed approach, named distributed delay efficient data aggregation scheduling (DEDAS-D) to solve the aggregation-scheduling problem in duty-cycled WSNs. The analysis indicates that our solution is a better approach to solve this problem. We conduct extensive simulations to corroborate our analysis and show that DEDAS-D outperforms other distributed schemes and achieves an asymptotic performance compared with centralized scheme in terms of data aggregation delay.

Delay-efficient data aggregation scheduling in duty-cycled wireless sensor networks

Data aggregation is an essential operation in wireless sensor networks (WSNs) in which sensed data are aggregated and transmitted to the sink. In many applications, reducing the latency of data aggregation is an important target. In addition, one of the primary challenges in WSNs is energy scarcity and reducing energy consumption is a problem. Recently, duty cycling, i.e., periodically switching on and off communication and sensing capabilities, has been considered to significantly reduce the sensors energy consumption and extend a network lifetime. In this paper, we consider the minimum-latency aggregation scheduling problem in duty-cycled WSNs. We propose a Delay-Efficient Data Aggregation Scheduling (DEDAS) scheme to generate a collision-free schedule and minimize the delay for data aggregation in duty-cycled WSNs. Our analysis and comprehensive simulation results indicate that our solution performs better than existing schemes.

Efficient Time Latency of Data Aggregation Based on Neighboring Dominators in WSNs

Data Aggregation is a fundamental activity in wireless sensor networks. Recent studies in this area focus on giving collision-free scheduling and finding the upper bound of delay time in aggregation. In this paper, we propose a new scheduling strategy, based on Neighboring Dominators, to minimize the time latency in data aggregation. With the new scheduling strategy, we mathematically prove that the upper bound of delay time in Data Aggregation is at most 12R+A-11. Here R is the network radius and A is the maximum node degree in communication graph of network. Theoretical analysis proves that our strategy is significantly better than the previously well known results with the upper bounds at 16R+A-14 or 24D+6A +16 time slots, where D is network diameter (D could be as large as 2R).

Maximizing lifetime for a sensor network

Network lifetime is a key characteristic in evaluating sensor networks. Sensor coverage and connectivity have been included in discussions on network lifetime. Many models and algorithms have been proposed to increase the lifetime of a sensor network. Most are based on switching sensors between sleep and active modes while maintaining coverage and network connectivity. Connected cover is a set of sensors that covers all targets and forms a connected graph. The problem is to find a set of connected covers and the durations of their activity so that all targets are covered during a maximal time period and the sum of the activity time intervals for each sensor is not greater than its lifetime. We propose a new heuristic approach to maximize the lifetime of a sensor network given a superfluous set of connected covers.