The stable marriage problem: structure and algorithms
The stable marriage problem: structure and algorithms
Modeling and analysis of stochastic systems
Modeling and analysis of stochastic systems
Mobility increases the capacity of ad hoc wireless networks
IEEE/ACM Transactions on Networking (TON)
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Strong approximations for Markovian service networks
Queueing Systems: Theory and Applications
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Gossip-Based Computation of Aggregate Information
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
The message delay in mobile ad hoc networks
Performance Evaluation - Performance 2005
A new networking model for biological applications of ad hoc sensor networks
IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
Algebraic gossip: a network coding approach to optimal multiple rumor mongering
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Performance modeling of epidemic routing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Capacity and delay tradeoffs for ad hoc mobile networks
IEEE Transactions on Information Theory
Fast Distributed Algorithms for Computing Separable Functions
IEEE Transactions on Information Theory
Detecting Hot Road Mobility of Vehicular Ad Hoc Networks
Mobile Networks and Applications
| Hi-index | 0.00 |
In this paper, we consider wireless mobile sensor networks under extreme environments where nodes: 1) have local knowledge; 2) have limited computational power; 3) make distributed decisions; and 4) move rapidly over time. Information dissemination in these networks (or gossip) can be modeled via epidemic models that analyze behavior of the system mimicking the way diseases spread (or even gossip for that matter). However, the limitation on computational power and energy of nodes forces us to consider explicit stopping criteria that are seldom done in the literature. Furthermore, harsh environments considered in this paper prevent nodes from transmitting sensed information at specified time slots and hence might cause a large variation in intertransmission time distribution. The objective of this paper is to characterize the dynamics of the information spread and obtain performance measures based on stochastic modeling. We start with modeling information flow using a Markov chain and obtain performance measures such as time to transfer information and fraction of nodes receiving information. Then, we provide a method to obtain those performance measures when the assumption on intertransmission time distribution is relaxed, e.g., time-varying transmission rates and nonexponential intertransmission time distributions, which makes our model more realistic. We make a curious finding in that, for our proposed model, the average fraction of nodes receiving information is a parameter-free constant. We also show that our model is scalable and effective.