Designing an asynchronous group communication middleware for wireless users

Abstract

We evaluate an asynchronous gossiping middleware for wireless users that propagates messages from any group member to all the other group members. This propagation can either be implemented through distributed mechanisms or can be mediated through servers. Our analysis of asynchronous mechanisms using wireless user availability traces from an university, corporation and a hot spot federation shows that the fundamental impediment to the system performance is the wireless user availability patterns. We then investigate the relative performance for several distributed as well as server mediated approaches. We show that pull mechanisms effectively randomizes the times when messages are propagated and thus achieves better performance than push based mechanisms. We then develop an adaptive approach that customizes the propagation frequency using the last session duration and show that this mechanism exhibits good performance when the required propagation intervals are large. We also show that for a given number of gossips, it is preferable to propagate messages to all available nodes rather than increasing the frequency while correspondingly reducing the number of nodes to propagate messages. Our results allow middleware developers to choose the appropriate propagation model to satisfy their application constraints.

MEGCOM: Min-Energy Group COMmunication in Multi-hop Wireless Networks

“…An interesting fact revealed by the simulations is that Algorithm 1 always performs better than Algorithm 2, although the latter has a better theoretical approximation ratio than the former (see Theorem 1 and Theorem 2). 3 We can attribute this effect to the fact that the guardian set is searched from a larger solution space in Algorithm 1 than in Algorithm 2, which should on average result in less internal nodes in the shared multicast tree constructed by Algorithm 1, hence a lower total energy consumption of a group communication session using the tree and a better performance of Algorithm 1 in average sense.…”

“…In a traditional setting (e.g., the Internet), investigations on group communication focus on the system reliability in the face of network failures or group member changes [2]. As the recent booming of multi-hop wireless networks for various purposes (e.g., wireless mesh networks to allow Internet access in remote areas or wireless sensor networks for habitat monitoring) further demand group communication to work on top of such networks (e.g., [3]), group communication is facing a new challenge: energy constraints for wireless nodes. As it is generally believed that the continuous development of the wireless technology will result in more and more wireless applications making use of group communication primitive (e.g., mobile social networking and gaming), designing energy-efficient group communication protocols has become imperative.One naive way for designing an energy-efficient group communication protocol is to employ the existing one-tomany multicast protocols.…”