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31
Real-Time power-aware routing in sensor networks
- In Proceeding of the IEEE International Workshop on Quality of Service (IWQoS
, 2006
"... Abstract — Many wireless sensor network applications must resolve the inherent conflict between energy efficient communication and the need to achieve desired quality of service such as end-to-end communication delay. To address this challenge, we propose the Real-time Power-Aware Routing (RPAR) pro ..."
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Cited by 57 (8 self)
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Abstract — Many wireless sensor network applications must resolve the inherent conflict between energy efficient communication and the need to achieve desired quality of service such as end-to-end communication delay. To address this challenge, we propose the Real-time Power-Aware Routing (RPAR) protocol, which achieves application-specified communication delays at low energy cost by dynamically adapting transmission power and routing decisions. RPAR features a power-aware forwarding policy and an efficient neighborhood manager that are optimized for resource-constrained wireless sensors. Moreover, RPAR addresses important practical issues in wireless sensor networks, including lossy links, scalability, and severe memory and bandwidth constraints. Simulations based on a realistic radio model of MICA2 motes show that RPAR significantly reduces the number of deadlines missed and energy consumption compared to existing real-time and energy-efficient routing protocols. I.
On broadcast authentication in wireless sensor networks
- In International Conference on Wireless Algorithms, Systems, and Applications (WASA 2006
, 2006
"... Abstract — Broadcast authentication is a critical security service in wireless sensor networks (WSNs), as it allows the mobile users of WSNs to broadcast messages to multiple sensor nodes in a secure way. Although symmetric-keybased solutions such as µTESLA and multilevel µTESLA have been proposed, ..."
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Cited by 45 (5 self)
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Abstract — Broadcast authentication is a critical security service in wireless sensor networks (WSNs), as it allows the mobile users of WSNs to broadcast messages to multiple sensor nodes in a secure way. Although symmetric-keybased solutions such as µTESLA and multilevel µTESLA have been proposed, they all suffer from severe energydepletion attacks resulting from the nature of delayed message authentication. This paper presents several efficient public-key-based schemes to achieve immediate broadcast authentication and thus avoid the security flaw inherent in the µTESLA-like schemes. Our schemes are built upon the unique integration of several cryptographic techniques, including the Bloom filter, the partial message recovery signature scheme and the Merkle hash tree. We prove the effectiveness and efficiency of the proposed schemes by a comprehensive quantitative analysis of their energy consumption in both computation and communication. I.
Exploring the energy-latency trade-off for broadcasts in energy-saving sensor networks
- in ICDCS
, 2005
"... Efficient information dissemination is essential for the operationality of sensor networks. However, one of the challenges to efficient information dissemination arises from only a random subset of nodes being active in any given time. This is mainly due to sensor networks employing powersaving tech ..."
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Cited by 25 (5 self)
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Efficient information dissemination is essential for the operationality of sensor networks. However, one of the challenges to efficient information dissemination arises from only a random subset of nodes being active in any given time. This is mainly due to sensor networks employing powersaving techniques to compensate the energy constraints of sensor nodes. Specifically, significant delay is incurred from any packet transmission attempt in a power-saving network that allow nodes periodically switch to sleep modes to conserve energy. In this paper, we propose a Probability-Based Broadcast Protocol (PBBF) that aims to provide fast broadcast propagation in the case of such networks. Simulation studies show that PBBF efficient and effective information dissemination with low latency while still maintaining high delivery ratios. 1.
A local data abstraction and communication paradigm for pervasive computing
- In Proc. of PerCom
, 2007
"... As sensor networks are increasingly used to support pervasive computing, we envision an instrumented environment that can provide varying amounts of information to mobile applications immersed within the network. Such a scenario deviates from existing deployments of sensor networks which are often h ..."
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Cited by 14 (11 self)
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As sensor networks are increasingly used to support pervasive computing, we envision an instrumented environment that can provide varying amounts of information to mobile applications immersed within the network. Such a scenario deviates from existing deployments of sensor networks which are often highly application-specific and funnel information to a central collection point. We instead target scenarios in which multiple mobile applications will leverage sensor network nodes opportunistically and unpredictably. Such situations require new communication abstractions that enable immersed devices to interact directly with available sensors, reducing both communication overhead and data latency. This paper introduces scenes, which applications create based on their communication requirements, abstract properties of the underlying network communication, and properties of the physical environment. This paper reports on the communication model, an initial implementation, and its performance in varying scenarios. 1.
A new routing metric for satisfying both energy and delay constraints in wireless sensor networks ,” The
- Journal of VLSI Signal Processing
, 2007
"... Besides energy constraint, wireless sensor networks should also be able to provide bounded communication delay when they are used to support real-time applications. In this paper, a new routing metric is proposed. It takes into account both energy and delay constraints. By mathematical analysis and ..."
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Cited by 14 (4 self)
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Besides energy constraint, wireless sensor networks should also be able to provide bounded communication delay when they are used to support real-time applications. In this paper, a new routing metric is proposed. It takes into account both energy and delay constraints. By mathematical analysis and simulations, we have shown the efficiency of this new routing metric. 1.
B.: Roadmap query for sensor network assisted navigation in dynamic environments. In
, 2005
"... Abstract. Mobile entity navigation in dynamic environments is an essential part of many mission critical applications like search and rescue and fire fighting. The dynamism of the environment necessitates the mobile entity to constantly maintain a high degree of awareness of the changing environment ..."
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Cited by 11 (5 self)
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Abstract. Mobile entity navigation in dynamic environments is an essential part of many mission critical applications like search and rescue and fire fighting. The dynamism of the environment necessitates the mobile entity to constantly maintain a high degree of awareness of the changing environment. This criteria makes it difficult to achieve good navigation performance by using just on-board sensors and existing navigation methods and motivates the use of wireless sensor networks (WSNs) to aid navigation. In this paper, we present a novel approach that integrates a roadmap based navigation algorithm with a novel WSN query protocol called Roadmap Query (RQ). RQ enables collection of frequent, up-todate information about the surrounding environment, thus allowing the mobile entity to make good navigation decisions. Simulation results under realistic fire scenarios show that in highly dynamic environments RQ outperforms existing approaches in both navigation performance and communication cost. We also present a mobile agent based implementation of RQ along with preliminary experimental results, on Mica2 motes. 1
A New Storage Scheme for Approximate Location Queries in Object Tracking Sensor Networks
- IEEE Trans. Parallel and Distributed Systems
, 2008
"... Abstract—Energy efficiency is one of the most critical issues in the design of wireless sensor networks. Observing that many sensor applications for object tracking can tolerate a certain degree of imprecision in the location data of tracked objects, this paper studies precision-constrained approxim ..."
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Cited by 10 (2 self)
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Abstract—Energy efficiency is one of the most critical issues in the design of wireless sensor networks. Observing that many sensor applications for object tracking can tolerate a certain degree of imprecision in the location data of tracked objects, this paper studies precision-constrained approximate queries that trade answer precision for energy efficiency. We develop an Energy-conserving Approximate StoragE (EASE) scheme to efficiently answer approximate location queries by keeping error-bounded imprecise location data at some designated storage node. The data impreciseness is captured by a system parameter called the approximation radius. We derive the optimal setting of the approximation radius for our storage scheme based on the mobility pattern and devise an adaptive algorithm to adjust the setting when the mobility pattern is not available a priori or is dynamically changing. Simulation experiments are conducted to validate our theoretical analysis of the optimal approximation setting. The simulation results show that the proposed EASE scheme reduces the network traffic from a conventional approach by up to 96 percent and, in most cases, prolongs the network lifetime by a factor of 2-5. Index Terms—Energy efficiency, data dissemination, data storage, location query, wireless sensor network. 1
Scenes: Abstracting Interaction in Immersive Sensor Networks
"... Pervasive computing deployments are increasingly using sensor networks to build instrumented environments that provide local data to immersed mobile applications immersed. These applications demand opportunistic and unpredictable interactions with local devices. While this direct communication has t ..."
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Cited by 5 (2 self)
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Pervasive computing deployments are increasingly using sensor networks to build instrumented environments that provide local data to immersed mobile applications immersed. These applications demand opportunistic and unpredictable interactions with local devices. While this direct communication has the potential to reduce both overhead and latency, it deviates significantly from existing uses of sensor networks that funnel information to a static central collection point. This pervasive computing driven perspective demands new communication abstractions that enable the required direct communication among mobile applications and embedded sensors. This paper presents the scene abstraction, which allows immersed applications to create dynamic distributed data structures over the immersive sensor network. A scene is created based on application requirements, properties of the underlying network, and properties of the physical environment. This paper details our work on defining scenes, providing an abstract model, an implementation, and an evaluation.
Amorphous Placement and Informed Diffusion for Timely Field Monitoring by Autonomous, Resource-Constrained, Mobile Sensors
"... Abstract—Personal communication devices are increasingly equipped with sensors for passive monitoring of encounters and surroundings. We envision the emergence of services that enable a community of mobile users carrying such resource-limited devices to query such information at remote locations in ..."
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Cited by 4 (2 self)
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Abstract—Personal communication devices are increasingly equipped with sensors for passive monitoring of encounters and surroundings. We envision the emergence of services that enable a community of mobile users carrying such resource-limited devices to query such information at remote locations in the field in which they collectively roam. One approach to implement such a service is directed placement and retrieval (DPR), whereby readings/queries about a specific location are routed to a node responsible for that location. In a mobile, potentially sparse setting, where end-to-end paths are unavailable, DPR is not an attractive solution as it would require the use of delay-tolerant (flooding-based store-carry-forward) routing of both readings and queries, which is inappropriate for applications with data freshness constraints, and which is incompatible with stringent device power/memory constraints. Alternatively, we propose the use of amorphous placement and retrieval (APR), in which routing and field monitoring are integrated through the use of a cache management scheme coupled with an informed exchange of cached samples to diffuse sensory data throughout the network, in such a way that a query answer is likely to be found close to the query origin. We argue that knowledge of the distribution of query targets could be used effectively by an informed cache management policy to maximize the utility of collective storage of all devices. Using a simple analytical model, we show that the use of informed cache management is particularly important when the mobility model results in a non-uniform distribution of users over the field. We present results from extensive simulations which show that in sparsely-connected networks, APR is more cost-effective than DPR, that it provides extra resilience to node failure and packet losses, and that its use of informed cache management yields superior performance.
An Information Theoretic Framework for Field Monitoring Using Autonomously Mobile Sensors
"... We consider a mobile sensor network monitoring a spatio-temporal field. Given limited cache sizes at the sensor nodes, the goal is to develop a distributed cache management algorithm to efficiently answer queries with a known probability distribution over the spatial dimension. First, we propose a n ..."
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Cited by 3 (2 self)
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We consider a mobile sensor network monitoring a spatio-temporal field. Given limited cache sizes at the sensor nodes, the goal is to develop a distributed cache management algorithm to efficiently answer queries with a known probability distribution over the spatial dimension. First, we propose a novel distributed information theoretic approach in which the nodes locally update their caches based on full knowledge of the space-time distribution of the monitored phenomenon. At each time instant, local decisions are made at the mobile nodes concerning which samples to keep and whether or not a new sample should be acquired at the current location. These decisions account for minimizing an entropic utility function that captures the average amount of uncertainty in queries given the probability distribution of query locations. Second, we propose a different correlation-based technique, which only requires knowledge of the second-order statistics, thus relaxing the stringent constraint of having a priori knowledge of the query distribution, while significantly reducing the computational overhead. It is shown that the proposed approaches considerably improve the average field estimation error by maintaining efficient cache content. It is further shown that the correlation-based technique is robust to model mismatch in case of imperfect knowledge of the underlying generative correlation structure.
