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226
SecureDAV: A secure data aggregation and verification protocol for sensor networks
- In Proceedings of the IEEE Global Telecommunications Conference
, 2004
"... Abstract — Sensor networks include nodes with limited computation and communication capabilities. One of the basic functions of sensor networks is to sense and transmit data to the end users. The resource constraints and security issues pose a challenge to information aggregation in large sensor net ..."
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Cited by 39 (0 self)
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Abstract — Sensor networks include nodes with limited computation and communication capabilities. One of the basic functions of sensor networks is to sense and transmit data to the end users. The resource constraints and security issues pose a challenge to information aggregation in large sensor networks. Bootstrapping keys is another challenge because public key cryptosystems are unsuitable for use in resource-constrained sensor networks. In this paper, we propose a solution by dividing the problem in two domains. First, we present a protocol for establishing cluster keys in sensor networks using verifiable secret sharing. We chose elliptic curve cryptosystems for security because of their smaller key size, faster computations and reductions in processing power. Second, we develop a Secure Data Aggregation and Verification (SecureDAV) protocol that ensures that the base station never accepts faulty aggregate readings. Integrity check of the readings is done using Merkle Hash Trees avoiding over-reliance on the cluster-heads. I.
Geocasting with guaranteed delivery in sensor networks
- IEEE Wireless Communications
, 2004
"... In a geocasting problem, a message is sent from one node to all the nodes located in a designated region. For example, monitoring center needs to contact all active sensors within a monitored area to either gather data from them periodically, or to provide its location to sensors covering certain ar ..."
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Cited by 30 (2 self)
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In a geocasting problem, a message is sent from one node to all the nodes located in a designated region. For example, monitoring center needs to contact all active sensors within a monitored area to either gather data from them periodically, or to provide its location to sensors covering certain area for event reporting. Intelligent flooding methods exist for this task when all active sensors belong to the monitored area. However, when a particular area containing only a small subset of active sensors needs to be monitored, the problem reduces to geocasting. Most existing geocasting solutions are shown not to guarantee delivery. We then describe three approaches to guarantee delivery. Two of them are face traversal schemes and are based on depthfirst search of the face tree and traversal of all faces that intersect the border of geocasting region, respectively. In the entrance zone multicasting based approach, the monitoring center divides entrance ring of geocast region into zones of diameter equal to the transmission radius. The problem is decomposed into multicasting toward centers of each zone, and flooding from these nodes. Improvements to all methods can be made by applying neighbor or area dominating sets and coverage, and converting nodes that are not selected to sleep mode. All solutions that guarantee delivery are reported here for the first time (except a message inefficient version of face tree traversal scheme). 1.
A Low-Latency and Energy-Efficient Algorithm for Convergecast in Wireless Sensor Networks
, 2003
"... In Wireless Sensor Networks (WSN) the process of dissemination of data among various sensors (broadcast)andcollection of data from all sensors (convergecast or data aggregation) are common communication operations. With increasing demands on efficient use of battery power, many efficient broadcast ..."
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Cited by 28 (0 self)
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In Wireless Sensor Networks (WSN) the process of dissemination of data among various sensors (broadcast)andcollection of data from all sensors (convergecast or data aggregation) are common communication operations. With increasing demands on efficient use of battery power, many efficient broadcast tree construction and channel allocation algorithms have been proposed. Generally convergecast is preceded by broadcast. Hence the tree used for broadcast is also used for convergecast. Our research shows that this approach is inefficient in terms of latency and energy consumption.
Fault Tolerant Energy Aware Data Dissemination Protocol in Sensor Networks
- In IEEE Dependable Systems and Networks Conference
"... In this paper we present a data dissemination protocol for efficiently distributing data through a sensor network in the face of node and link failures. Our work is motivated by the SPIN protocol which uses metadata negotiation to minimize data transmissions. We propose a protocol called Shortest Pa ..."
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Cited by 26 (4 self)
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In this paper we present a data dissemination protocol for efficiently distributing data through a sensor network in the face of node and link failures. Our work is motivated by the SPIN protocol which uses metadata negotiation to minimize data transmissions. We propose a protocol called Shortest Path Minded SPIN (SPMS) in which every node has a zone defined by its maximum transmission radius. A node which is a data source advertises the availability of data to all the nodes in its zone using a metadata descriptor. Any interested node requests the data and gets sent the data using multi-hop communication via the shortest path. The failure of any node in the path is detected and recovered using backup routes. We build simulation models to compare SPMS against SPIN. Different scenarios including mobility and node failures are simulated. The simulation results show that SPMS reduces the delay over 10 times and consumes 30 % less energy in the static failure free scenario. Even with the addition of mobility, SPMS outperforms SPIN by energy gains between 5 % and 21%. An analytical model is also constructed to compare the two protocols under a simplified topology.
Design and Analysis of Hybrid Indirect Transmissions (HIT) for Data Gathering in Wireless Micro Sensor Networks
- In ACM SIGMOBILE Mobile Computing and Communications Review
, 2004
"... Sensor networks have many potential applications in biology, physics, medi-cine, and the military. One major challenge in sensor networks is to maximize network life under the constraint of limited power supply. The paper addresses energy-efficiency in the context of routing and data gathering. A ne ..."
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Cited by 24 (1 self)
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Sensor networks have many potential applications in biology, physics, medi-cine, and the military. One major challenge in sensor networks is to maximize network life under the constraint of limited power supply. The paper addresses energy-efficiency in the context of routing and data gathering. A new protocol is proposed: Hybrid Indirect Transmission (HIT). HIT is based on a hybrid ar-chitecture that consists of one or more clusters, each of which is based on mul-tiple, multi-hop indirect transmissions. In order to minimize both energy con-sumption and network delay, parallel transmissions are used both among mul-tiple clusters and within a cluster. This is made possible by having each sensor independently compute a medium access controlling TDMA schedule. The com-putation within each sensor is intelligent yet simple. Formal analysis shows that it requires O(n) space and O(nu logn) time complexities, and O(1) setup mes-sages prior to the computation, where n is the total number of sensors. HIT does not require sensor nodes with CDMA capability, or the remote base sta-tion to compute a data gathering schedule. Performance is evaluated by simu-lating and comparing HIT with three other existing protocols, including Low
Data gathering tours in sensor networks
- IN IPSN
, 2006
"... A basic task in sensor networks is to interactively gather data from a subset of the sensor nodes. When data needs to be gathered from a selected set of nodes in the network, existing communication schemes often behave poorly. In this paper, we study the algorithmic challenges in efficiently routing ..."
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Cited by 24 (6 self)
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A basic task in sensor networks is to interactively gather data from a subset of the sensor nodes. When data needs to be gathered from a selected set of nodes in the network, existing communication schemes often behave poorly. In this paper, we study the algorithmic challenges in efficiently routing a fixed-size packet through a small number of nodes in a sensor network, picking up data as the query is routed. We show that computing the optimal routing scheme to visit a specific set of nodes is NP-complete, but we develop approximation algorithms that produce plans with costs within a constant factor of the optimum. We enhance the robustness of our initial approach to accommodate the practical issues of limited-sized packets as well as network link and node failures, and examine how different approaches behave with dynamic changes in the network topology. Our theoretical results are validated via an implementation of our algorithms on the TinyOS platform and a controlled simulation study using Matlab and TOSSIM.
Mobile Agent Based Wireless Sensor Networks
"... Abstract—Recently, mobile agents have been proposed for efficient data dissemination in sensor networks. In the traditional client/server-based computing architecture, data at multiple sources are transferred to a destination; whereas in the mobile-agent based computing paradigm, a taskspecific exec ..."
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Cited by 23 (6 self)
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Abstract—Recently, mobile agents have been proposed for efficient data dissemination in sensor networks. In the traditional client/server-based computing architecture, data at multiple sources are transferred to a destination; whereas in the mobile-agent based computing paradigm, a taskspecific executable code traverses the relevant sources to gather data. Mobile agents can be used to greatly reduce the communication cost, especially over low bandwidth links, by moving the processing function to the data rather than bringing the data to a central processor. This paper proposes to use the mobile agent paradigm for reducing and aggregating data in a planar sensor network architecture. The proposed architecture is called mobile agent based wireless sensor network (MAWSN). Extensive simulation shows that MAWSN exhibits better performance than client/server communications in terms of energy consumption and the packet delivery ratio. However, MAWSN has a longer end-to-end latency than client/server communications in certain conditions. Index Terms—mobile agent, energy efficient, aggregate, data dissemination, wireless sensor networks I.
Networked wireless sensor data collection: Issues, challenges, and approaches
- IEEE Commun. Surv. Tutor
"... Abstract—Wireless sensor networks (WSNs) have been applied to many applications since emerging. Among them, one of the most important applications is Sensor Data Collections, where sensed data are collected at all or some of the sensor nodes and forwarded to a central base station for further proces ..."
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Cited by 23 (0 self)
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Abstract—Wireless sensor networks (WSNs) have been applied to many applications since emerging. Among them, one of the most important applications is Sensor Data Collections, where sensed data are collected at all or some of the sensor nodes and forwarded to a central base station for further processing. In this paper, we present a survey on recent advances in this research area. We first highlight the special features of sensor data collection in WSNs, by comparing with both wired sensor data collection network and other WSN applications. With these features in mind, we then discuss the issues and prior solutions on the utilizations of WSNs for sensor data collection. Based on different focuses of previous research works, we describe the basic taxonomy and propose to break down the networked wireless sensor data collection into three major stages, namely, the deployment stage, the control message dissemination stage and the data delivery stage. In each stage, we then discuss the issues and challenges, followed by a review and comparison of the previously proposed approaches and solutions, striving to identify the research and development trend behind them. In addition, we further discuss the correlations among the three stages and outline possible directions for the future research of the networked wireless sensor data collection. Index Terms—Wireless sensor network, sensor data collection, deployment, data gathering, message dissemination. I.
Maximizing Lifetime of Sensor Surveillance Systems
- IEEE/ ACM Trans. Networking
, 2006
"... Abstract—This paper addresses the maximal lifetime scheduling problem in sensor surveillance systems. Given a set of sensors and targets in an area, a sensor can watch only one target at a time, our task is to schedule sensors to watch targets and forward the sensed data to the base station, such th ..."
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Cited by 23 (3 self)
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Abstract—This paper addresses the maximal lifetime scheduling problem in sensor surveillance systems. Given a set of sensors and targets in an area, a sensor can watch only one target at a time, our task is to schedule sensors to watch targets and forward the sensed data to the base station, such that the lifetime of the surveillance system is maximized, where the lifetime is the duration that all targets are watched and all active sensors are connected to the base station. We propose an optimal solution to find the target-watching schedule for sensors that achieves the maximal lifetime. Our solution consists of three steps: 1) computing the maximal lifetime of the surveillance system and a workload matrix by using the linear programming technique; 2) decomposing the workload matrix into a sequence of schedule matrices that can achieve the maximal lifetime; and 3) determining the sensor surveillance trees based on the above obtained schedule matrices, which specify the active sensors
Distributed computing paradigms for collaborative signal and information processing in sensor networks
- International Journal of Parallel and Distributed Computing
, 2004
"... Abstract — In sensor networks, collaborative processing between multiple sensor nodes is essential in order to complement for each other’s sensing capability, tolerate faults, and provide reliable information. The client/server-based paradigm is typical for distributed processing. However, it is not ..."
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Cited by 21 (3 self)
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Abstract — In sensor networks, collaborative processing between multiple sensor nodes is essential in order to complement for each other’s sensing capability, tolerate faults, and provide reliable information. The client/server-based paradigm is typical for distributed processing. However, it is not the most efficient in the context of sensor networks. In this paper, we present a mobileagent-based paradigm to carry out collaborative processing, where instead of each sensor node sending local information to a processing center, as is typical in the client/server-based computing, the processing code is moved to the sensor nodes through mobile agents. This approach has great potential in providing energy-efficient and scalable collaborative processing with low latency. We design two metrics (execution time and energy consumption) and use simulation tools to quantitatively measure the performance of different computing models in collaborative processing. Experimental results show that the mobile agent paradigm performs much better when the number of nodes is large while the client/server paradigm is advantageous when the number of nodes is small. Based on this result, we develop a cluster-based hybrid computing paradigm to combine the advantages of both paradigms. We analyze two different scenarios in hybrid computing and simulation results show that there is always one scenario that performs better than either the client/server- or mobile-agent-based paradigm.
