Sharif Digital Repository

We study the problem of power efficient tracking interval management for distributed target tracking wireless sensor networks (WSNs). We first analyze the performance of a distributed target tracking network with one moving object, using a quantitative mathematical analysis. We show that previously proposed algorithms are efficient only for constant average velocity objects; however, they do not ensure an optimal performance for moving objects with acceleration. Towards an optimal performance, first, we derive a closed-form mathematical expression for the estimation of the minimal achievable power consumption by an optimal adaptive tracking interval management algorithm. This can be used as... 

Data aggregation is a key, yet time-consuming functionality in wireless sensor networks (WSNs). Multi-channel design is a promising technique to alleviate interference as a primary reason for long latency of TDMA aggregation scheduling. Indeed, it provides more potential of parallel transmissions over different frequency channels, thus minimizing time latency. In this paper, we focus on designing a multi-channel minimum latency aggregation scheduling protocol, named MC-MLAS, using a new joint approach for tree construction, channel assignment, and transmission scheduling. To our best knowledge, this is the first work in the literature which combines orthogonal channels and partially... 

Wireless sensor networks (WSNs) use energy for their sensing, computation, and communication. To increase the lifetime of the network, sensor nodes are equipped with energy storage devices. Recharging of their batteries is not possible in most applications. Therefore, energy consumption needs to be monitored and limited to increase the energy consumption performance of the network. The communication module uses the highest amount of energy in a WSN. Among several methods offered to reduce the energy consumption, data compression has the highest effect on the energy usage by reducing the number of bits to be broadcasted. This paper illustrates an energy consumption reduction in WSN by... 

Data aggregation is a key, yet time-consuming functionality introduced to conserve energy in wireless sensor networks (WSNs). In this paper, to minimize time latency, we focus on aggregation scheduling problem and propose an efficient distributed algorithm that generates a collision-free schedule with the least number of time slots. In contrast to others, our approach named FAST mainly contributes to both tree construction, where the former studies employ Connected 2-hop Dominating Sets, and aggregation scheduling that was previously addressed through the Competitor Sets computation. We prove that the latency of FAST under the protocol interference model is upper-bounded by 12R+Δ-2, where R... 

Reliability and energy consumption are two of the main constraints in wireless sensor networks (WSNs). In this paper, a novel energy efficient and high speed error control scheme is introduced that is based on the Redundant Residue Number System (RRNS) allowing real-time application of WSNs. The proposed approach employs a new 3-moduli set {22n+1, 2 2n1-1, 2n- 1 } and an efficient reverse converter which relies on the Mixed Radix Conversion (MRC) algorithm and achieves significant improvements both in terms of conversion delay and hardware design. In order to obtain error controllability, two-redundant-moduli set 23n+1 - 1, 24n+1 - 1 is also added to the main 3-moduli set. The theoretical... 

In this letter, both the number of participating nodes and spatial dispersion are incorporated to establish a bi-objective optimization problem for maximizing the quality of aggregation under interference and delay constraints in tree-based wireless sensor networks (WSNs). The formulated problem is proved to be NP-hard with respect to Weighted-sum scalarization and a distributed heuristic aggregation scheduling algorithm, named SDMAX, is proposed. Simulation results show that SDMAX not only gives a close approximation of the Pareto-optimal solution, but also outperforms the best, to our knowledge, existing alternative proposed so far in the literature  

Wireless sensor networks (WSNs) consume energy for their sensing, computation, and communication. To extend the lifetime of the network, sensor nodes are equipped with energy storage devices. Recharging of their batteries is impossible in most applications. Therefore, energy consumption needs to be monitored and limited to extend the high performance operation of the network. In this network, the communication module consumes the highest amount of energy. This paper demonstrates that among several methods offered to reduce the energy consumption, data compression has the highest effect on the energy usage by reducing the number of bits to be broadcasted. To determine the energy efficiency of... 

To scavenge the energy from the environment and extend the network lifetime, some wireless sensor networks (WSNs) have been equipped with energy harvesters recently. However, the variable amount of environmental energy can affect the reliability of energy harvesting wireless sensor networks (EH-WSNs). In addition, data transmission over a wireless media is vulnerable. Hence, utilizing suitable error control schemes are necessary to improve the reliability. Regarding this point, Automatic Repeat Request (ARQ) and Cooperative ARQ (C-ARQ) schemes are applied in this generation of WSNs. Conventional ARQ as well as C-ARQ scheme are considered and examined through simulation. A comparative... 

Many applications that utilise wireless sensor networks (WSNs) require essentially secure communication. However, WSNs suffer from some inherent weaknesses because of restricted communication and hardware capabilities. Key management is the crucial important building block for all security goals in WSNs. Most existing researches tried to assign keys assuming homogeneous network architecture. Recently, a few key management models for heterogeneous WSNs have been proposed. In this study, the authors propose a dynamic key management framework based on elliptical curve cryptography and signcryption method for heterogeneous WSNs. The proposed scheme has network scalability and sensor node (SN)... 

Presently, the urgency of creating efficient system to tackle natural hazards such as tsunamis, earthquakes, landslides and floods to cite just a few, have originated that Wireless Sensor Networks (WSNs) play an increasingly important role in the natural hazards scenario as an efficient early warning system, sometimes in synergy with satellites-GMES (Global Monitoring Earth Systems) and also with mobile robotics. Their integration into the web scenario, giving rise to the sensor-web technology, provides even more power to the intrinsic strengths of WSNs. The WSNs application in post-disaster scenarios is also an emerging challenging issue. In this paper the fundamental technology concepts of... 

Wireless Sensor Networks (WSNs) have been weaved into the fabric of our daily lives. The foremost impediment in the rapid development of these networks is the energy limitation which inhibits them from meeting specific application requirements. Recently, the advances in energy harvesting technology have made it possible to replenish the energy of sensors via external sources. Energy Harvesting-Wireless Sensor Networks (EH-WSNs) are being transformed from a visionary concept into reality. However, this concept is still in its infancy and calls for extensive research to cater to the needs of WSNs. For future progress of EH-WSNs, Medium Access Control (MAC) layer has undoubtedly a decisive role... 

Wireless sensor networks (WSNs) comprise a large number of small sensor nodes scattered across limited geographical areas. The nodes in such networks carry sources of limited and mainly unchangeable energy. Therefore, it is necessary that these networks operate under energy efficient protocols and structures. Energy efficient clustering algorithms have been developed to reduce the networks energy consumption and extend its lifetime. This paper presents an innovative cluster-based communication protocol for WSNs. In order to reduce communication overhead, the authors propose an Energy Aware Clustering Hierarchy Protocol that creates a multi-level hierarchical structure to adequately route and... 

Minimizing energy consumption is the most important concern in wireless sensor networks (WSNs). To achieve this, clustering and prediction methods can enjoy the inherent redundancy of raw data and reduce transmissions more effectively. In this paper, we focus on designing a prediction-based approach, named PDC, to mainly contribute in data-aware clustering. It exploits both spatial and temporal correlations to form highly stable clusters of nodes sensing similar values. Here, the sink node uses only the local prediction models of cluster heads to forecast all readings in the network without direct communication. To the best of our knowledge, PDC is a novel energy efficient approach which... 

Limited energy in each node is the major design constraint in wireless sensor networks (WSNs). To overcome this limit, wireless rechargeable sensor networks (WRSNs) have been proposed and studied extensively over the last few years. In a typical WRSN, batteries in sensor nodes can be replenished by a mobile charger that periodically travels along a certain trajectory in the sensing area. To maximize the charged energy in sensor nodes, one fundamental question is how to control the traveling velocity of the charger. In this paper, we first identify the optimal velocity control as a key design objective of mobile wireless charging in WRSNs. We then formulate the optimal charger velocity... 

Many Random Key Distribution (RKD) schemes have been proposed in the literature to enable security applications in Wireless Sensor Networks (WSNs). A main security aspect of RKD schemes is their resistance against node capture attacks, since compromising the sensors and capturing their keys is a common risk in such networks. We propose a new method, based on a 2-Dimensional Hash Chain (2DHC), that can be applied on any RKD scheme to improve their resilience. Our method maintains the flexibility and low cost features of RKD schemes and it doesn't require any special-purpose hardware or extra memory to store keys in the sensors. We demonstrate that our approach significantly increases the... 

Development of Internet of things (IoT) applications brings a new movement to the functionality of wireless sensor networks (WSNs) from only environment sensing and data gathering to collaborative inferring and ubiquitous intelligence. In intelligent WSNs, nodes collaborate to exchange the information needed to achieve the required inference or smartness. Efficiency or correctness of many smart applications rely on efficient, timely, reliable, and ubiquitous inference of information which may continually change in interaction with other nodes. In this paper, we introduce a framework which provides a generic solution for such common ubiquitous inferences. This framework brings the reliability... 

Energy harvesters are used in today's Wireless Sensor Networks (WSNs) to harvest energy from the environment. Although an energy harvester can provide a supply source with a much greater lifetime than a battery, the amount of available energy for an energy harvesting system is a random variable. Furthermore, the proper management of energy harvesters has a considerable impact on reliability. It has been observed that cooperative error control mechanisms like Cooperative Automatic Repeat Request (C-ARQ) and Cooperative Hybrid ARQ (C-HARQ) can be used for improving the energy management and reliability in Energy Harvesting WSNs (EH-WSNs). Recently, the impact of C-ARC mechanism has been... 

The prime shortcoming of Wireless Sensor Networks (WSNs) is their energy constraint. The main energy consumer in a sensor node is its radio transmitter. One of the most effective methods to reduce the data transmission rate is data prediction. By data prediction, the amount of transmitted data is reduced; which results in energy saving and the longevity of the network life. Environmental variations almost have similar effects on different sensor sources in a sensor device. So, considering the correlation between different sources reduces the noise impact and increases data prediction accuracy. In this paper, temporal and multi-source correlations are used, to reduce data transmission in... 

Data aggregation is an effective technique which is introduced to conserve energy by reducing packet transmissions in wireless sensor networks (WSNs). In addition, it is possible to consume less energy by using the spatial correlation and redundancy of data in dense networks to form clusters of nodes sensing similar values and, in turn, transmit one data packet per cluster. In this paper, we propose a Data-Aware Clustering and Aggregation scheme (DACA) to manage the energy constraint in a query-driven WSN. The DACA selects cluster head nodes by forming a new factor as a function of three parameters including the residual energy, the data value, and the number of neighbors at each node.... 

Wireless Sensor Networks (WSNs) are prone to faults due to battery depletion of nodes. A node failure can disturb routing as it plays a key role in transferring sensed data to the end users. This paper presents a Fault-Tolerant and Energy-Aware Mechanism (FTEAM), which prolongs the lifetime of WSNs. This mechanism can be applied to cluster-based WSN protocols. The main idea behind the FTEAM is to identify overlapped nodes and configure the most powerful ones to the sleep mode to save their energy for the purpose of replacing a failed Cluster Head (CH) with them. FTEAM not only provides fault tolerant sensor nodes, but also tackles the problem of emerging dead area in the network. Our...