Exploiting link correlation for core-based dissemination in wireless sensor networks

Wireless Sensor Networks (WSNs) are popular in smart homes to implement context-aware and intelligent services. Due to fixing bugs and adding new functions, the software on sensor nodes needs to be updated depending on efficient bulk data dissemination. Existing page transfer of data dissemination protocols employ pipelining technique to achieve spatial multiplexing. The conventional pipelining inefficiency, however, becomes a bottleneck in terms of dissemination delay and communication overhead. In this paper, we propose SAPM, a novel Self-Adjusting Pipelining Mechanism for efficient bulk data dissemination. By considering the impact of link correlation, detecting accumulated pages in sensor nodes, and carefully selecting the number of pages to request, SAPM shortens the dissemination delay effectively and reduces communication overhead to improve current bulk data dissemination protocols' performance. Our evaluation results on test bed experiments and extensive simulations show that SAPM reduces the completion time of state-of-the-art bulk data dissemination protocols by 27.8% on average compared to naive solution and the number of transmissions by 17.4% on average under high link correlation while having a low memory overhead.

A multichannel code distribution protocol for remote reprogramming in WSNs

The technique of distributed storage coding has been widely used in wireless sensor networks for increasing the robustness of data storage and efficiency of data retrieval. Existing works mainly focus on scenarios in which each storage node stores a linear combination of a subset of K data packets generated by different source nodes. By solving the linear equations, a collector can recover all the K data packets with high probability. This paper explores the problem of flexible and efficient data dissemination and retrieval in wireless sensor networks. Our scheme exploits the broadcast nature of wireless transmission and improves the traditional random walk algorithm for efficient data dissemination. Furthermore, through the use of Fountain codes in data encoding, it enables a mobile collector to recover up-to-date data generated by any subset of source nodes. Specifically, by querying any t(1 + ε) storage nodes at the t-th time slot, the target data can be retrieved without having to decode all the source packets. Simulation results validate our analysis and show that the proposed schemes are flexible and efficient.

The goal of this paper is to design and implement an efficient data dissemination algorithm for wireless sensor networks. The proposed approach requires nodes in a network to publish their characteristics to their neighboring nodes. Each node selects its parent node for data forwarding using a method similar to natural selection. Fitness score for selection is locally calculated considering several characteristics of a neighboring node such as: battery level, distance, and hierarchy level. The main goal of this algorithm is to extend the wireless sensor network lifetime by distributing the traffic load among the nodes that have higher probabilities of predicted survival, which is identified by their fitness score. In addition, this approach can provide a framework to study the emergent behaviors of networks when different local rules for node selection are applied.

Security and efficient data dissemination over wireless network has been the focus of research in academic, military and commercial domains for many years. Unfortunately, proposed security solutions for data dissemination over wireless network are not efficient enough. In this work, a novel security and efficient data dissemination scheme which integrates authentication into a SE-Raptor (security enhanced Raptor) codes is investigated. In SE-Raptor codes, encoding packets with degree one are encoded again, and many promiscuous packets are took part in encoding. Simulation results show that the proposed method has better performance in terms of encoding ratio, degree ratio, encoding and decoding efficiency. Additionally, our analysis shows that data confidentiality, bogus data protection and deny of service properties are provided by the proposed scheme.

Network re-programming in wireless sensor networks is an essential facility, especially in practice, for deploying and maintaining highly dynamic sensor nodes. This paper proposes an efficient way to update whole binary image based on layered architecture with multi-hop network protocol. The layered architecture utilizes 3 different memories including flash, RAM and EEPROM. The network dissemination protocol is based on hierarchical routing and support practical considerations such as sleep/wake-up mechanism for energy saving.

We present a new mechanism called Elon for enabling efficient and long-term reprogramming in wireless sensor networks. Elon reduces the transferred code size significantly by introducing the concept of replaceable component. It avoids the cost of hardware reboot with a novel software reboot mechanism. Moreover, it significantly prolongs the reprogramming lifetime by avoiding flash writes for TelosB nodes. Experimental results show that Elon transfers up to 120--389 times less information than Deluge, and 18-42 times less information than Stream. The software reboot mechanism that Elon applies reduces the rebooting cost by 50.4%-53.87% in terms of beacon packets, and 56.83% in terms of unsynchronized nodes. In addition, Elon prolongs the reprogramming lifetime by a factor of 2.3.

Wireless sensor network-based (WSN-based) applications need an efficient and reliable data dissemination service to facilitate maintenance, management and data distribution tasks. As WSNs nowadays are becoming pervasive and data intensive, bulk data dissemination protocols have been extensively studied recently. This paper provides a comprehensive survey of the state-of-the-art bulk data dissemination protocols. The large number of papers available in the literature propose various techniques to optimize the dissemination protocols. Different from the existing survey works which separately explores the building blocks of dissemination, our work categorizes the literature according to the optimization purposes: Reliability, Scalability and Transmission/Energy efficiency. By summarizing and reviewing the key insights and techniques, we further discuss on the future directions for each category. Our survey helps unveil three key findings for future direction: (1) The recent advances in wireless communications (e.g., study on cross-technology interference, error estimating codes, constructive interference, capture effect) can be potentially exploited to support further optimization on the reliability and energy efficiency of dissemination protocols; (2) Dissemination in multi-channel, multi-task and opportunistic networks requires more efforts to fully exploit the spatial-temporal network resources to enhance the data propagation; (3) Since many designs incur changes on MAC layer protocols, the co-existence of dissemination with other network protocols is another problem left to be addressed.

In a wireless sensor network, the sensing and data transmission for sensors will cause energy depletion, which will lead to the inability to complete the tasks. To solve this problem, wireless rechargeable sensor networks (WRSNs) have been developed to extend the lifetime of the entire network. In WRSNs, a mobile charging robot (MR) is responsible for wireless charging each sensor battery and collecting sensory data from the sensor simultaneously. Thereby, MR needs to traverse along a designed path for all sensors in the WRSNs. In this paper, dual-side charging strategies are proposed for MR traversal planning, which minimize the MR traversal path length, energy consumption, and completion time. Based on MR dual-side charging, neighboring sensors in both sides of a designated path can be wirelessly charged by MR and sensory data sent to MR simultaneously. The constructed path is based on the power diagram according to the remaining power of sensors and distances among sensors in a WRSN. While the power diagram is built, charging strategies with dual-side charging capability are determined accordingly. In addition, a clustering-based approach is proposed to improve minimizing MR moving total distance, saving charging energy and total completion time in a round. Moreover, integrated strategies that apply a clustering-based approach on the dual-side charging strategies are presented in WRSNs. The simulation results show that, no matter with or without clustering, the performances of proposed strategies outperform the baseline strategies in three respects, energy saving, total distance reduced, and completion time reduced for MR in WSRNs.

Recently, wireless sensor network (WSN) has become a formidable force in almost all areas of our everyday life. However, there are still many issues with wireless sensor networks among which is the energy problem. One of the numerous techniques that have been introduced as a way of solving the problem of energy deficit inherent in a WSN is sleep scheduling. Sleep scheduling allows sensor nodes to periodically take turns to sleep in order to minimize energy cost in a WSN. Apparently, Overemission in a WSN is one of the main causes of energy drainage in sensor nodes. Traditional schemes fail to take into consideration the sleeping timetable of other nodes; hence they let transmitter nodes repeatedly send RTS preamble packets and similar control packets to sleeping nodes. Our proposed sleep scheduling scheme addresses this problem from a whole new perspective using a system called Designated Sensor Node (DSN) mechanism. The DSN scheme significantly reduces flooding of the network with unnecessary control packets. The effect in turn leads to the minimization of unnecessary energy waste in a WSN.

The advantages of deploying mobile sinks (MSs) in wireless sensor networks (WSNs) have attracted tremendous attention recently, because mobility of a sink provides an efficient method to improve data gathering performance in WSNs. However, in such kind of WSN, the efficiency of data dissemination is obviously affected by the trajectory of the MS. Therefore, optimal moving schemes of the MS have been studied in many researches. Nevertheless, in many cases, the trajectory of the MS is not able to change ideally as previous studies assumed but depending on the environmental conditions. In this paper, we focus on the efficiency of data gathering in WSN with a MS whose trajectory cannot change ideally and propose a new data diffusion scheme - implementing a new Pre-Diffusion Algorithm (PDA) in a hierarchical WSN aimed at improving data gathering efficiency. This hierarchical WSN is composed of several clusters, and datatransmission is done by higher powered cluster head (CH) node. Our scheme predetermines the cluster area where the MS is going to arrive in most probability in next period of time. MS fulfills data converging in the cluster head (CH)whose distance to the MS may the smallest compared with other CHs when data gathering starts. Thus more data can be collected with less trajectory length of MS. Simulation results show that our proposed scheme improves data gathering efficiency as compared to conventional scheme.

Multi-hop over-the-air reprogramming is essential for remote installation of software patches and upgrades in wireless sensor networks (WSNs). Several recent coding-based reprogramming protocols have been proposed to enable efficient code dissemination in high packet loss environments. An accurate and formal analysis of the performance of these protocols, however, has not been studied sufficiently in the literature. In this paper, we present a novel high-fidelity analytical model based on the shortest path algorithm to measure the completion time by incorporating overhearing and packet coding. This model can be applied to any coding-based reprogramming protocol by substituting the coding part with protocol specific operations. We conduct extensive testbed experiments to evaluate the performance of our proposed model. Based on the analytical and numerical experiments, we find that 1) overhearing causes significant reduction of the completion time in dense wireless sensor networks, particularly, it reduces 50-70 percent of the total completion time when the packet reception rate is 0.896; 2) coding delay plays a key role in the total completion time compared to the communication delay when the packet coding parameters are selected appropriately, for example, the communication delay is about 65 percent of the coding delay when the number of packets per page is 16 for the finite field size 28 ; 3) the total completion time can be minimized when the number of packets per page is close to 24 and the finite field size is close to 24 .

Wireless Sensor Networks (WSNs) consist of a large number of small and low cost sensor nodes powered by small batteries and equipped with various sensing devices. Usually, for many applications, once a WSN is deployed, probably in an inhospitable terrain, it is expected to gather the required data for quite some time, say for years. Since each sensor node has limited energy, these nodes are usually put to sleep to conserve energy, and this helps to prolong the network lifetime. There are two major approaches to sleep scheduling of sensor nodes, viz. (i) random (ii) synchronized. Any sleep scheduling scheme has to ensure that data can always be routed from source to sink. In this paper, we propose a novel approach for sleep scheduling of sensor nodes using a tree and an energy aware routing protocol which is integrated with the proposed sleep scheduling scheme. The tree is rooted at the sink node. The internal nodes of the tree remain awake and the leaf nodes are made to sleep. This provides an assured path from any node to the sink node. The tree is periodically reconstructed considering the remaining energy of each node with a view to balance energy consumption of nodes, and remove any failed nodes from the tree. The proposed approach also considerably reduces average energy consumption rate of each node as we are able to put more number of nodes to sleep in comparison to other approaches. Additional fault-tolerance is provided by keeping two paths from each node towards the sink. Extensive simulation studies of the proposed routing protocol has been carried out using Castalia simulator, and its performance has been compared with that of a routing protocol, called GSP, which incorporates sleep scheduling using random approach. The simulation results show that the proposed approach has longer network lifetime in comparison to that provided by GSP, and the energy consumption of nodes is also balanced.

Directional antennas have numerous advantages over traditional omnidirectional antennas, which include more spatial reuse, extended range, less interference, and less energy consumption. Directional antennas introduce deafness and new hidden terminal problems. Deafness may cause more collisions, and hidden terminal problems may result in more retransmissions, poor quality of service, more energy consumption, and less packet delivery ratio. Hence, it is important to design of an effective medium access protocol specifically for directional antennas in order to reap the benefits of directional antennas while managing deafness and hidden terminal problems, otherwise the challenges can adversely affect system performance. In wireless sensor networks, the sensors are battery powered with limited supply of energy. Therefore, energy efficient protocols and solutions are immensely important with the desired goal of extending the network lifetime longer than what is possible through the omnidirectional antennas. In this thesis, I have proposed an energy efficient scheduled directional medium access control protocol (DTRAMA) which is specially designed for the wireless sensor nodes which use directional antennas in wireless sensor networks. It is a traffic adaptive scheduled medium access protocol in which nodes create their transmission and sleep schedules on the basis of their traffic. Scheduled medium access for packet transmission is used to address the deafness and hidden terminal problems caused by the use of directional communication in contention based MAC protocols. Use of directional antenna reduces interference which indirectly improves packet delivery ratio by improving the signal to noise ratio and by reducing the packet error rate. DTRAMA is energy efficient: firstly because the nodes use directional data communication which requires lower node transmit power than the omnidirectional data communication for the same transmission range; and secondly, because the nodes schedule their sleep period to reduce idle listening and overhearing which improves energy efficiency. In DTRAMA, sleep schedule of the node is traffic adaptive which is essential to maximize the sleep period. The node, by using spatial reuse checks, reuses the wireless medium to the maximum extent to reap the spatial reuse benefits of the directional antenna. The nodes reduce their packet latency through spatial reuse. Through simulation and by using different topologies, I have compared the performance of DTRAMA with those of omnidirectional schedule MAC protocol (TRAMA) and contention based directional MAC protocol (DMAC), which clearly shows that DTRAMA outperforms TRAMA and DMAC in packet delivery ratio and outperforms TRAMA in terms of packet latency.

Directional antennas have numerous advantages over traditional omnidirectional antennas, which include more spatial reuse, extended range, less interference, and less energy consumption. Directional antennas introduce deafness and new hidden terminal problems. Deafness may cause more collisions, and hidden terminal problems may result in more retransmissions, poor quality of service, more energy consumption, and less packet delivery ratio. Hence, it is important to design of an effective medium access protocol specifically for directional antennas in order to reap the benefits of directional antennas while managing deafness and hidden terminal problems, otherwise the challenges can adversely affect system performance. In wireless sensor networks, the sensors are battery powered with limited supply of energy. Therefore, energy efficient protocols and solutions are immensely important with the desired goal of extending the network lifetime longer than what is possible through the omnidirectional antennas. In this thesis, I have proposed an energy efficient scheduled directional medium access control protocol (DTRAMA) which is specially designed for the wireless sensor nodes which use directional antennas in wireless sensor networks. It is a traffic adaptive scheduled medium access protocol in which nodes create their transmission and sleep schedules on the basis of their traffic. Scheduled medium access for packet transmission is used to address the deafness and hidden terminal problems caused by the use of directional communication in contention based MAC protocols. Use of directional antenna reduces interference which indirectly improves packet delivery ratio by improving the signal to noise ratio and by reducing the packet error rate. DTRAMA is energy efficient: firstly because the nodes use directional data communication which requires lower node transmit power than the omnidirectional data communication for the same transmission range; and secondly, because the nodes schedule their sleep period to reduce idle listening and overhearing which improves energy efficiency. In DTRAMA, sleep schedule of the node is traffic adaptive which is essential to maximize the sleep period. The node, by using spatial reuse checks, reuses the wireless medium to the maximum extent to reap the spatial reuse benefits of the directional antenna. The nodes reduce their packet latency through spatial reuse. Through simulation and by using different topologies, I have compared the performance of DTRAMA with those of omnidirectional schedule MAC protocol (TRAMA) and contention based directional MAC protocol (DMAC), which clearly shows that DTRAMA outperforms TRAMA and DMAC in packet delivery ratio and outperforms TRAMA in terms of packet latency.