The emergence of mobile computing provides the ability to access information at any time and place. However, as mobile computing environments have inherent factors like power, storage, asymmetric communication cost, and bandwidth limitations, efficient query processing and minimum query response time are definitely of great interest. This survey groups a variety of query optimization and processing mechanisms in mobile databases into two main categories, namely: (i) query processing strategy, and (ii) caching management strategy. Query processing includes both pull and push operations (broadcast mechanisms). We further classify push operation into on-demand broadcast and periodic broadcast. Push operation (on-demand broadcast) relates to designing techniques that enable the server to accommodate multiple requests so that the request can be processed efficiently. Push operation (periodic broadcast) corresponds to data dissemination strategies. In this scheme, several techniques to improve the query performance by broadcasting data to a population of mobile users are described. A caching management strategy defines a number of methods for maintaining cached data items in clients' local storage. This strategy considers critical caching issues such as caching granularity, caching coherence strategy and caching replacement policy. Finally, this survey concludes with several open issues relating to mobile query optimization and processing strategy.
This paper describes a new classification system for real-time monitoring of physical activity, which is able to detect body postures (lying, sitting, and standing) and walking speed with data acquired from three wearable biaxial accelerometer sensors deployed in a wireless body sensor network. One sensor is waist-mounted while the remaining two are attached to the respective thighs. Two studies were conducted for the evaluation of the system, with each study involving five human subjects. Results from the first study indicated an overall accuracy of 100% for classification of lying, sitting, standing, and walking across a series of 40 randomly chosen tasks. In our system, estimated walking speeds are used to distinguish between different types of movement activity (walking, jogging, and running), and the accuracy of its estimation was evaluated in our second study which gave an overall mean-square error (MSE) of 1.76 (km/h)(2).
In a decentralised system like P2P where each individual peers are considerably autonomous, the notion of mutual trust between peers is critical. In addition, when the environment is subject to inherent resource constraints, any efficiency efforts are essentially needed. In light of these two issues, we propose a novel trustworthy-based efficient broadcast scheme in a resource-constrained P2P environment. The trustworthiness is associated with the peer's reputation. A peer holds a personalised view of reputation towards other peers in four categories namely SpEed, Correctness, qUality, and Risk-freE (SeCuRE). The value of each category constitutes a fraction of the reliability of individual peer. Another factor that contributes to the reliability of a peer is the peer's credibility concerning trustworthiness in providing recommendation about other peers. Our trust management scheme is applied in conjunction with our trust model in order to detect malicious and collaborative-based malicious peers. Knowledge of trustworthiness among peers is used in our proposed broadcast model named trustworthy-based estafet multi-point relays (TEMPR). This model is designed to minimise the communication overhead between peers while considering the trustworthiness of the peers such that only trustworthy peer may relay messages to other peers. With our approach, each peer is able to disseminate messages in the most efficient and reliable manner.
Abstract. The increase number of mobile users in wireless environment affects query access time substantially. To minimise the query access time, one possible way is to employ data broadcasting strategy. In this paper, we propose cost models for both query access time over broadcast channel and on-demand channel. We examine the cost models to find optimum number of broadcast items in a channel while utilising query access time over on-demand channel as a threshold point. The optimum number indicates a point to split the broadcast cycle and allocate the data items in the new channel or else the on-demand channel outperforms the broadcast channel. The cost model involves several factors that dynamically change the optimum number of broadcast items like request arrival rate, service rate, size of data item, size of request, and bandwidth. Simulation model is developed to verify the performance of the cost model. This paper focuses on request that returns a single data item.
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