In a mobile Peer-to-Peer (P2P) environment, where inherent resource constraints (e.g. battery, bandwidth and computing power) exist, the notion of reliability and efficiency especially around communication of messages between peers is a crucial factor. In this paper, we introduce a trustworthy token-passing multi-point relays (TOP) data dissemination scheme for moving objects in wireless ad-hoc networks. The proposed scheme encompasses the trustworthy model and location-based scheduling technique capable of determining the most optimal schedule for the target peers to receive messages based on the location and mobility parameter. The performance of the proposed approach is compared against the existing state of techniques namely pure flooding and Trustworthiness-based Broadcast (TBB) scheme. The experimental evaluation includes a number of metrics, such as transmission cost, computational cost and message deliverability, of which the results showed promising performance of the proposed scheme.

In a mobile environment, data broadcast paradigm has been recognised as an effective and scalable mechanism to disseminate frequently requested information to a large number of mobile users. This paper presents the design and implementation of a power preserving mobile broadcast system. The broadcast system is designed to serve transitive queries or queries that access related data items belonging to different tables in the relational databases. The focus of this paper is revolved around the implementation of three specific data broadcast schemes, namely: (i) a filtering technique for mobile device to perform transitive queries and display the desired data from incoming multiple entity types broadcast data items, (ii) the index broadcast scheme to predict the arrival of the desired data so that power utilization can be minimized, and (iii) multiple channel environments to allow mobile device to tune into multiple broadcast channels to receive the desired data. We showcase the efficacy of these data broadcast schemes through the development of the prototype system with a share indices price application.

Data broadcast with its scalability feature provides a strong backbone for the digital information delivery. Such a feature is especially significant for mobile users with inherent power limitations in asymmetric communication environments. This paper presents a specific broadcast ordering scheme supported by advanced structure and access mechanism for ad-hoc queries in mobile data broadcast environments. The proposed scheme aims to minimize both query-access and tuning times by specifying a new message and ordering structure. As a proof of concept, we carry out experimentation of the proposed scheme in comparison with the conventional models. The result of the experiments are presented and discussed in the paper.

The increasing use of mobile communications has raised many issues of decision support and resource allocation. A crucial problem is how to solve queries of Reverse Nearest Neighbor (RNN). An RNN query returns all objects that consider the query object as their nearest neighbor. Existing methods mostly rely on a centralized base station. However, mobile P2P systems offer many benefits, including self-organization, fault-tolerance and load-balancing. In this study, we propose two P2P algorithms focusing on bichromatic RNN queries, in which mobile query objects and static objects of interest are of two different categories, based on a boundary polygon around the mobile query object. The Exhaustive Search Algorithm makes use of all information from the peers to aim at high accuracy rate while the Optimized Search Algorithm reduces the number of queried peers. The algorithms are evaluated in MiXiM simulation framework with a real dataset. The results show the practical feasibility of the P2P approach in solving bichromatic RNN queries for mobile networks.

A participatory mobile sensing system is designed to enable clients to voluntarily collect environmental data using embedded sensors and a mobile device while going about their daily activities. Due to the spatio-temporal nature of the data, and the significant benefits of the data to the general public, it is necessary to employ an efficient and effective query processing model for the mobile clients to access the data that can be visualized via an interactive multimedia interface. This article introduces a unified on-demand and data broadcast model to serve queries in the context of a mobile sensing system. The contributions of this article include the following: (i) it presents a novel data structure and indexing method to support the system; (ii) it provides flexibility for the client to issue query using on-demand or broadcast channel according to the server load and broadcast schedule; (iii) it enables new data access and processing for the mobile client; and (iv) it is designed for a multiple channels/receivers environment in a 4G wireless network. The proposed model uses a holistic query processing approach for the mobile sensing system that offers substantial efficiency and autonomy for mobile clients when retrieving data. The results of the experiments undertaken affirm the effectiveness of its performance.

This paper introduces a novel clustering-based broadcast scheduling technique for mobile nearest-neighbor (NN) query processing in cyber physical systems. An efficient index structure is presented to guide mobile clients to the NN-objects. The proposed broadcast scheduling and indexing is aimed at minimizing query access time and energy consumption of the clients when retrieving NN-objects through wireless channels. We have experimentally studied the proposed scheme and its comparison with the state-of-the-art methods. The results suggest the efficacy of our proposed approach in offering minimum latency and energy consumption, which is critically important especially for resource-constrained wireless environments.

There is a growing focus on 24/7 cardiac monitoring that leverages state of the art mobile phones and commercial-off-the-shelf (COTS) wearable bio-sensors. While many signal processing techniques for mobile ECG analysis have been developed, these techniques tend to be computationally intensive. In this paper, we propose, develop and evaluate a resource-aware and energy-efficient time series analysis technique for real-time ECG analysis on mobile devices based on the well-known SAX (Symbolic Aggregate Approximation) representation for time series termed RA-SAX.

Together with the advance of positioning and mobile technologies, P2P query processing has attracted a growing interest number of location-aware applications such as answering kNN queries in Mobile Ad-hoc Networks. It not only overcomes drawbacks of centralized paradigms; for example single point of failure and bottle-neck issues, but more importantly harnesses power of peers' collaboration. In this research, we propose a pure mobile P2P query processing with novel searching and validating algorithms to find kNNs without support from the base station. The simulation results show that our paradigm can make use of data sharing from peers to save energy consumption on querying at least six times compared with centralized and hybrid paradigms in a reasonable mean latency of processing time for networks with high density of moving objects.

This paper proposes a new global index structure and processing for location-dependent queries in mobile broadcast environments. The proposed scheme consists of two essential elements for addressing spatial queries in broadcast databases. These two elements are: (i) determine the client's location in relevant to the spatial model adopted by the broadcast scheme, and (ii) obtain the required object, which corresponds to the location of the client as determined by the model. The global index's concept will enhance the efficiency of the model. We explore the effectiveness of the proposed index scheme in single and multi channel environments. Performance comparisons with the earlier work through simulated-experiments have also been carried out and the results found have been promising.

This article introduces MobiSense, a novel mobile health monitoring system for ambulatory patients. MobiSense resides in a mobile device, communicates with a set of body sensor devices attached to the wearer, and processes data from these sensors. MobiSense is able to detect body postures such as lying, sitting, and standing, and walking speed, by utilizing our rule-based heuristic activity classification scheme based on the extended Kalman (EK) Filtering algorithm. Furthermore, the proposed system is capable of controlling each of the sensor devices, and performing resource reconfiguration and management schemes (sensor sleep/wake-up mode). The architecture of MobiSense is highlighted and discussed in depth. The system has been implemented, and its prototype is showcased. We have also carried out rigorous performance measurements of the system including real-time and query latency as well as the power consumption of the sensor nodes. The accuracy of our activity classifier scheme has been evaluated by involving several human subjects, and we found promising results.

Recent advances in wireless communication and sensor technologies have opened up a new paradigm in healthcare industry. More and more attentions in the wireless body area network (WBAN) have been received recently. However, the limited network resources constrain the application development in WBAN. In this paper, we present a service-specific middleware architecture to bridge the gap between the application development and the underlying network sensor devices. The proposed middleware is able to provide functions including network initialization and registration, service announcement, sensor actuation and control for flexible multiple modalities data acquisition, and real-time network service management. The middleware has been implemented and tested with a healthcare monitoring test-bed using Imperial College sensor nodes.

In a wireless environment, data broadcast paradigm has been recognized as an effective and scalable mechanism to disseminate frequently requested information to a large number of clients. This paper presents the development of a multiple entity types wireless broadcast database system. The broadcast system is designed to serve transitive queries or queries that access related data items belonging to different entity types. The broadcast data are retrieved from a central database server. We apply three different data broadcast schemes including: (i), filtering technique for mobile device to perform transitive queries and display the desired data from incoming multiple entity types broadcast data items; (ii), the index broadcasting scheme designed to predict the arrival of the desired data to appropriately execute power conserving mode; (iii), incorporate multiple channel environments to allow mobile device to tune into multiple broadcast channels to receive the desired data. The proposed model uses a share indices price context to demonstrate the effective use of these data broadcast schemes.

Data broadcasting is a scalable mechanism to disseminate information to a large number of mobile clients in a wireless environment. Our paper concerns with developing a data broadcasting system in a mobile environment, which involves data and index dissemination. The broadcasted data is retrieved from a database server. Subsequently, these data may be broadcasted periodically or aperiodically. As wireless environment inherent resource limitations, the use of indexing scheme will provide efficient data retrieval. We use share indices price context to demonstrate our proposed models. The models are developed using wireless ad-hoc network infrastructure.

Broadcast indexing is necessary to be applied in a wireless broadcast environment as such the scheme helps mobile clients to find the desired data instances efficiently. This is particularly important considering the inherent limitations in mobile environment. In this paper, we present a global indexing scheme for location dependent queries. The proposed scheme is designed to serve queries in which the query result is relevant to client's location. Global indexing scheme aims to minimise index access time while having all the advantages of index broadcasting. We develop a simulation model to find out the access time performance of global indexing scheme as compared to non-global indexing scheme. Additionally, we analyse the efficiency of valid scope used in the global index scheme as compared with an existing valid scope. It is found that global index performs substantially better than the existing indexing concept.

Data broadcasting strategy is known as a scalable way to disseminate information to mobile users. However, with a very large set of broadcast items, the query access time of mobile clients raise accordingly, due to high waiting time for mobile clients to find their data of interest. One possible solution is to split the database information into several broadcast channels. In this paper, we introduce taxonomy of index dissemination for multibroadcast channel based on B* tree structure. We consider three indexing schemes namely: (i) nonreplicated indexing scheme (NRI), (ii) partially-replicated indexing scheme (PRI), and (iii) fully-replicated indexing scheme (FRI). Simulation model is developed to find out the access time performance of each scheme.