Data Dissemination In Mobile Research Articles

Cellular Traffic Offloading through Opportunistic Communications Based on Human Mobility

The rapid increase of smart mobile devices and mobile applications has led to explosive growth of data traffic in cellular network. Offloading data traffic becomes one of the most urgent technical problems. Recent work has proposed to exploit opportunistic communications to offload cellular traffic for mobile data dissemination services, especially for accepting large delayed data. The basic idea is to deliver the data to only part of subscribers (called target-nodes) via the cellular network, and allow target-nodes to disseminate the data through opportunistic communications. Human mobility shows temporal and spatial characteristics and predictability, which can be used as effective guidance efficient opportunistic communication. Therefore, based on the regularity of human mobility we propose NodeRank algorithm which uses the encounter characteristics between nodes to choose target nodes. Different from the existing work which only using encounter frequency, NodeRank algorithm combined the contact time and inter-contact time meanwhile to ensure integrity and availability of message delivery. The simulation results based on real-world mobility traces show the performance advantages of NodeRank in offloading efficiency and network redundant copies.

Reducing latency through efficient channel allocation methods for multiversion data dissemination in mobile computing environment

This paper focuses on channel allocation methods for multiversion data dissemination in mobile computing systems in which maximizing data currency (minimizing staleness) and minimizing the mean response time are of equal importance as providing consistent data items to mobile transactions. We propose broadcast marshalling method that clusters data to be broadcast, depending on their access frequencies, to reduce mean response time of the mobile clients. We consider two basic multiversion data organizations, namely vertical and horizontal data organizations and it uses an efficient mobile data compression technique, with minimal impact on the client, to efficiently use the low bandwidth of mobile communication systems and to reduce the mean access delay for data items and minimize the response times of the requests from the mobile clients. The broadcast and on-demand channels have different access performance under different system parameters and that a mobile cell should use a combination of both to obtain optimal access time for a given workload and system parameters. We study the data access efficiency of three channel configurations: i) all channels are used as on-demand channels (exclusive on-demand), ii) all channels are used for broadcast (exclusive broadcast) and iii) some channels are on-demand channels and some are broadcast channels (hybrid). Simulations on obtaining the optimal channel allocation, with two different Multiversion data organizations combined with compression scheme, were conducted and the result shows that the method significantly improves the system performance.

Efficient index caching for data dissemination in mobile computing environments

Due to the limited power supply of mobile devices, much research has been done on reducing the power consumption of mobile devices in mobile computing environments. Since supporting indices on the broadcast data items can effectively reduce the power consumption of the mobile clients, most of the existing research on data broadcasting has focused on designing efficient indexing schemes. In this paper, we propose to cache indices on the mobile clients and to use cached indices to facilitate the access of the broadcast data items. To manage the cache usage of the mobile clients, we propose two cache management policies. The lower-level-index-first policy caches the index nodes that are at the lower level of the index tree, while the cut-plane-first policy caches the index nodes that belong to a cut-plane of the index tree. Through experiments, we compare the performance of the two proposed policies with some existing policies in terms of tuning time and access time. The experiments show that index caching significantly reduces the tuning time of a mobile client without increasing its access time. In terms of tuning time, the experiments show that, when the access pattern of a mobile client is not skew, the cut-plane-first policy outperforms the lower-level-index first policy, LRU and LRFU. On the contrary, when the mobile client has a small cache and its access pattern is skew, the lower-level-index-first policy outperforms the cut-plane-first policy, LRU and LRFU. In terms of access time, the lower-level-index first policy outperforms the cut-plane-first policy, LRU and LRFU.

A study on channel allocation for data dissemination in mobile computing environments

This paper studies channel allocation methods for data dissemination through broadcast and on-demand channels. Analytical models and cost formulae for exclusive broadcast channels and exclusive on-demand channels are provided. Based on the models, we further derive cost models for dynamic channel allocation methods and propose a channel adaptation algorithm for optimizing system performance. The channel adaptation algorithm can be executed in O(n) time, where n is the number of data items in the database. Performance evaluation shows that the channel allocation algorithm produces optimal channel allocation which significantly improves the system performance under various parameter settings.