Abstract Wireless body sensor networks (WBSNs) enable a broad range of applications for continuous and real‐time health monitoring and medical assistance. Programming WBSN applications is a complex task especially due to the limitation of resources of typical hardware platforms and to the lack of suitable software abstractions. In this paper, SPINE (signal processing in‐node environment), a domain‐specific framework for rapid prototyping of WBSN applications, which is lightweight and flexible enough to be easily customized to fit particular application‐specific needs, is presented. The architecture of SPINE has two main components: one implemented on the node coordinating the WBSN and one on the nodes with sensors. The former is based on a Java application, which allows to configure and manage the network and implements the classification functions that are too heavy to be implemented on the sensor nodes. The latter supports sensing, computing and data transmission operations through a set of libraries, protocols and utility functions that are currently implemented for TinyOS platforms. SPINE allows evaluating different architectural choices and deciding how to distribute signal processing and classification functions over the nodes of the network. Finally, this paper describes an activity monitoring application and presents the benefits of using the SPINE framework. Copyright © 2010 John Wiley & Sons, Ltd.

Rapid development of wireless body sensor network (WBSN) applications can be enabled by suitable domain-specific frameworks which are usually organized in two parts: a base-station-side (or coordinator) and a sensor-node-side. While the former can be based on the Java language so being highly portable, the latter is usually highly dependent on the exploited sensor platform. Available state of the art frameworks follow such an organization and, in particular, the current version of SPINE is based on TinyOS and can be only used to effectively develop collaborative WBSN applications for TinyOS-based sensor platforms. To develop SPINE-based applications for new sensor platforms, the SPINE framework should be re-implemented for each new sensor platform to be exploited. This not only increases development efforts but also enforces SPINE-oriented developers to become skilled on the low-level programming abstractions provided by a new employed sensor platform. In this paper we discuss issues related to platform-independent development of collaborative WBSN applications and, specifically, describe the requirements, architecture and first implementation experiences of SPINE2 which aims at reaching a very high platform independency and raising the level of the used programming abstractions by providing a task-oriented programming model. The paper also discusses how such a task-oriented model enables dynamic task assignment and holistic collaborative task execution also for resource-constrained environments such as tiny sensor nodes.

SPINE (signal processing in node environment) is a framework for the development of body sensor network (BSN) applications. It provides developers of signal processing algorithms with APIs and libraries of protocols, utilities and data processing functions. Hence, it offers application developers new abstractions that improve interoperability and allow to reduce development time. This paper presents the architecture and the capabilities of the SPINE framework, and shows its use in the development of a real-time activity monitoring system prototype.

To ease large-scale realization of agent applications there is an urgent need for frameworks, methodologies and toolkits that support the effective development of agent systems. Moreover, since one of the main tasks for which agent systems were invented is the integration between heterogeneous software, independently developed agents should be able to interact successfully. In this paper, we present JADE (Java Agent Development Environment), a software framework to build agent systems for the management of networked information resources in compliance with the FIPA specifications for inter-operable intelligent multi-agent systems. The goal of JADE is to simplify development while ensuring standard compliance through a comprehensive set of system services and agents. JADE can then be considered to be an agent middle-ware that implements an efficient agent platform and supports the development of multi-agent systems. It deals with all the aspects that are not peculiar to agent internals and that are independent of the applications, such as message transport, encoding and parsing, or agent life-cycle management. Copyright © 2001 John Wiley & Sons, Ltd.

An image coding scheme using the discrete cosine transform is analyzed when the transform coefficients are vector quantized. The coding method is based on the known scheme proposed by Chen and Smith (1977) which sorts the picture blocks into classes according to the level of image activity. The coding scheme is modified to allow for vector quantization of the ac coefficients, in particular a pyramid vector quantizer (PVQ) is used. This is based on the statistical and geometric properties of a Laplacian source which, in fact, is the best model for the ac coefficients of the two-dimensional discrete cosine transform (2D-DCT) of an image. A method for forming almost statistically independent vectors is also suggested and improves quantization performance. Images are encoded with both the PVQ and standard scalar quantizer transform coders, demonstrating that the PVQ coder reduces the mean square encoding error and improves image quality. In particular, emphasis is given to how the use of fractional bit rates affects the objective and subjective gains obtained. The results presented (i.e. mean square error values and printed images) have been obtained experimentally, working with a statistical criterion in a group of images whose size was in accordance with the 50 Hz CCIR Recommendation 601 Standard.>

A new effective adaptive coding scheme for data compression of images is presented. It is based on a reduction of the spatial, temporal and statistical redundancy. Inter-frame motion compensation technique was used to take advantage of the image temporal correlation. A unitary 2D-DCT was performed on each (8x 8) pixel block in order to exploit spatial correlation and in order to decorrelate the block elements and to make the relative quantization error subjectively less disturbing. The Rate Distortion Function of a Laplacian source was used as a classification strategy by relating a block to a coding bit rate in accordance with its energy. The a.c. transform coefficients were vector quantized by using the pyramidal vector quantizer based on the cubic lattice. Compression ratios in the 8 — 12 range give a distribution quality for colour image sequences according to the CCIR Rec. 601 (12-20 Mbit/sec) or HDTV sequences (50-70 Mbit/sec). Experimental results obtained by computer simulations are presented and the influence of the motion compensation and the vector quantization on the objective error are analysed.