Latency Optimal Broadcasting in Noisy Wireless Mesh Networks

In this paper, we adopt a new noisy wireless network model introduced very recently by Censor-Hillel et al. in [ACM PODC 2017, CHHZ17]. More specifically, for a given noise parameter $p\in [0,1],$ any sender has a probability of $p$ of transmitting noise or any receiver of a single transmission in its neighborhood has a probability $p$ of receiving noise. In this paper, we first propose a new asymptotically latency-optimal approximation algorithm (under faultless model) that can complete single-message broadcasting task in $D+O(\log^2 n)$ time units/rounds in any WMN of size $n,$ and diameter $D$. We then show this diameter-linear broadcasting algorithm remains robust under the noisy wireless network model and also improves the currently best known result in CHHZ17 by a $\Theta(\log\log n)$ factor. In this paper, we also further extend our robust single-message broadcasting algorithm to $k$ multi-message broadcasting scenario and show it can broadcast $k$ messages in $O(D+k\log n+\log^2 n)$ time rounds. This new robust multi-message broadcasting scheme is not only asymptotically optimal but also answers affirmatively the problem left open in CHHZ17 on the existence of an algorithm that is robust to sender and receiver faults and can broadcast $k$ messages in $O(D+k\log n + polylog(n))$ time rounds.Comment: arXiv admin note: text overlap with arXiv:1705.07369 by other author

Wireless communication protocol architectures for nanosensor networks

Thesis (M.S.) University of Alaska Fairbanks, 2004Recent developments in micro fabrication and nanotechnology will enable the inexpensive manufacturing of massive numbers of tiny computing elements with sensors. New programming paradigms are required to obtain organized and coherent behavior from the cooperation of large numbers of sensor nodes. The individual nodes are identical, randomly placed and unreliable. They communicate with a small local neighborhood via wireless broadcast. In such environments, where individual nodes have limited resources, aggregating the node into groups is useful for specialization, increased robustness, and efficient resource allocation. In this paper, an application-specific self-organization protocol stack is developed. The clustering process is divided into phases. The first phase is to know the neighbor nodes. The second phase is to set up the cluster and routing. A 'find maximum clique algorithm' is used to set up clusters. A back off method is used to set up the hop field and routing. Group leaders set up a TDMA schedule for steady state operation. This schedule ensures that there is no conflict among in the same cluster and between clusters. Direct-sequence spread spectrum (DS-SS) is used to avoid inter-group conflict. The limited power resource is a challenge in nanosensor networks. This paper uses two different ways to analyze energy consumed in nanosensor networks, energy cost field and bit flow method. Sensor node deployment, cluster size, and propagation condition effect are discussed in this paper by those two methods respectively