Data-centric storage in sensornets
ACM SIGCOMM Computer Communication Review
Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Data-centric storage in sensornets with GHT, a geographic hash table
Mobile Networks and Applications
Data-centric routing and storage in sensor networks
Wireless sensor networks
Revisiting the TTL-based controlled flooding search: optimality and randomization
Proceedings of the 10th annual international conference on Mobile computing and networking
Maximum lifetime routing in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Combs, needles, haystacks: balancing push and pull for discovery in large-scale sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Comparative analysis of push-pull query strategies for wireless sensor networks
DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
The capacity of wireless networks
IEEE Transactions on Information Theory
Is data-centric storage and querying scalable?
Proceedings of the 4th international conference on Embedded networked sensor systems
Traffic Scheduling to Prolong the Lifetime of Sensor Networks
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
Balancing Push and Pull for Efficient Information Discovery in Large-Scale Sensor Networks
IEEE Transactions on Mobile Computing
Information fusion for wireless sensor networks: Methods, models, and classifications
ACM Computing Surveys (CSUR)
SDIP3: structured and dynamic information push and pull protocols for distributed sensor networks
DCOSS'07 Proceedings of the 3rd IEEE international conference on Distributed computing in sensor systems
Dynamic random replication for data centric storage
Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
Diffusion-based approach to deploying wireless sensor networks
International Journal of Sensor Networks
STARR-DCS: Spatio-temporal adaptation of random replication for data-centric storage
ACM Transactions on Sensor Networks (TOSN)
Hi-index | 0.00 |
We use a constrained optimization framework to derive fundamental scaling laws for both unstructured sensor networks (which use blind sequential search for querying) and structured sensor networks (which use efficient hash-based querying). We find that the scalability of a sensor network's performance depends upon whether or not the increase in energy and storage resources with more nodes is outweighed by the concomitant application-specific increase in event and query loads. Let m be the number of events sensed by a network over a finite period of deployment, q the number of queries for each event, and N the size of the network. Our key finding is that q1/2•m must be O(N1/4)for unstructured net-works, and q2/3•m must be O(N1/2)for structured networks, to ensure scalable network performance. These conditions determine (i) whether or not the energy requirement per node grows without bound with the network size for a fixed-duration deployment, (ii) whether or not there exists a maximum network size that can be operated for a specified duration on a fixed energy budget, and (iii) whether the network lifetime increases or decreases with the size of the network for a fixed energy budget. We discuss the practical implications of these results for the design of hierarchical two-tier wireless sensor networks.