Wireless sensor networks can be used in various fields, e.g., military and civil applications. The technique of saving energy to prolong the life of sensor nodes is one of main challenges to resource-constrained sensor networks. Therefore, in-network aggregation of data has been proposed in resource-constrained environments for energy efficiency. Most previous works on in-network aggregation only support a one-dimensional data (e.g., MIN and MAX). To support a multi-dimensional data, the skyline query is used. The skyline query returns a set of points that are not dominated by any other point on all dimensions. The majority of previous skyline query processing methods (e.g., BNL and BBS) work on centralized storage. Centralized query processing methods do not have merits in terms of energy efficiency in high event rate environments. In this paper, we propose new algorithm of in-network processing for the skyline queries. The proposed algorithm reduces the communication cost and evenly distributes load. The experimental results show the advantages of our algorithm over in-network aggregation in terms of improving energy efficiency.

With the growth of wireless computing and the popularity of eXtensible Markup Language (XML), wireless XML data management is emerging as an important research area. In this paper, cache invalidation methodology with XML update is addressed in wireless computing environments. A family of XML cache invalidation strategies, called S-XIR, D-XIR and E-XIR, is suggested. Using S-XIR and D-XIR, the unchanged part of XML data, only its structure changes, can be effectively reused in client caching. E-XIR, which uses prefetching, can further improve access time. Simulations are carried out to evaluate the proposed methodology; they show that the proposed strategies improve both tuning time and access time significantly. In particular, the proposed strategies are on average about 4 to 12 times better than the previous approach in terms of tuning time.

Broadcasting in wireless mobile computing environments is an effective technique to disseminate information to a massive number of clients equipped with powerful, battery operated devices. To conserve the usage of energy, which is scarce resource, the information to be broadcast must be organized so that the client can selectively tune in at the desired portion of the broadcast. In this letter, the power efficient behavior of a predeclaration-based transaction processing in mobile broadcast environments is examined. The analytical studies have been performed to observe the effectiveness of predeclaration-based transaction processing combined with selective tuning ability in mobile broadcast environments.

In this letter, a new estimation filtering is proposed when a delay between signal generation and signal estimation exists. The estimation filter is developed under a maximum likelihood criterion using only the finite observations on the delay interval. The proposed estimation filter is represented in both matrix form and iterative form. It is shown that the filtered estimate has good inherent properties such as time-invariance, unbiasedness and deadbeat. Via numerical simulations, the performance of the proposed estimation filtering is evaluated by the comparison with that of the existing fixed-lag smoothing, which shows that the proposed approach could be appropriate for fast estimation of signals that vary relatively quickly. Moreover, the on-line computational complexity of the proposed estimation filter is shown to be maintained at a lower level than the existing one.

This letter proposes a group-based distributed air index (called GDI) using two-leveled groups by partitioning the identifiers of data items to reduce the size of the index. GDI provides both global and local views of data items and multiple pointers to data items in a single access to an index. Simulation results show that GDI outperforms the existing index in terms of multiple data access, energy conservation and data waiting time.

It is observed, surprisingly, that existing nearest neighbor search methods in wireless data broadcast may not work effectively on mobile clients with very limited memory space. To resolve this problem, a novel method for nearest neighbor search is introduced in the context of a representative of indexes, the grid-partition index, in wireless data broadcast. In the proposed scheme, a mobile client performs the nearest neighbor search by making a sequential access to index packets according to their broadcast order over a wireless channel. The performance evaluation demonstrates that our approach substantially outperforms limited memory versions of existing methods in terms of access time, while retaining a good energy conservation.

Caching of frequently accessed data has been shown to be a useful technique for reducing congestion on the narrow bandwidth of wireless channels. However, traditional client/server strategies for supporting transactional cache consistency, which require extensive communications between a client and a server, are not appropriate in a wireless mobile database. This paper proposes two, simple but effective, transactional cache consistency protocols for mobile read-only transactions by utilizing the broadcast-based solutions for the problem of invalidating caches. The novelty of our approach is that the consistency check on accessed data and the commitment protocol are implemented in a truly distributed fashion as an integral part of cache invalidation process. The applicability of proposed techniques is also examined by an analytical study.