Peer‐based automatic configuration of pervasive applications

Abstract

Pervasive computing envisions seamless support for user tasks through cooperating devices that are present in an environment. Fluctuating availability of devices, induced by mobility and failures, requires mechanisms and algorithms that allow applications to adapt to their ever‐changing execution environments without user intervention. To ease the development of adaptive applications, Becker et al. (3) have proposed the peer‐based component system PCOM. This system provides fundamental mechanisms to support the automated composition of applications at runtime. In this article, we discuss the requirements on algorithms that enable automatic configuration of pervasive applications. Furthermore, we show how finding a configuration can be interpreted as Distributed Constraint Satisfaction Problem. Based on this, we present an algorithm that is capable of finding an application configuration in the presence of strictly limited resources. To show the feasibility of this algorithm, we present an evaluation based on simulations and real‐world measurements and we compare the results with a simple greedy approximation.

Direct Backtracking: An Advanced Adaptation Algorithm for Pervasive Applications

“…In this paper, we present a new centralized configuration algorithm called Direct Backtracking (DBT) that can be employed on resource-rich devices to configure pervasive applications on near-by resource-poor devices. This complements our previous work on purely decentralized configuration [5] and enables a range of configuration solutions with different degrees of decentralization since both approaches may be combined to produce a hybrid configuration system.…”

“…We compared Direct Backtracking to Synchronous Backtracking (SBT), the centralized version of Asynchronous Backtracking [7] that was used previously for distributed application configuration [5]. We chose to compare DBT to SBT as this is the best centralized algorithm that is applicable to the problem of adapting pervasive applications without excessive memory waste and computation overhead.…”

“…The adaptation of tree-based applications can be mapped to a Constraint Satisfaction Problem (CSP) [5]. In case of a fully distributed application configuration, this problem can be solved by distributed algorithms from the domain of Artificial Intelligence [7].…”

Handling Dynamic QoS Requirements in a Pervasive System

“…This management focuses primarily on usage privileges and QoS. Similar work has been done on the automatic configuration of applications (Handte et al [21]). However, since web services are inherently static, little work has been done on composition management of services with volatile availability.…”

Handling Personalized Redirection in a Wireless Pervasive Computing System with Different Approaches to Identity

“…The goa l of pe r va s i ve c omput i ng i s t o pr ovi de a n i nt e l l i ge nt e nvi r onme nt t o e na bl e t he us e r t o ma na ge t hi s s i t ua t i on wi t h mi ni ma l i nt e r ve nt i on [ 2] , [ 3] . Thi s i nc l ude s de a l i ng wi t h s e r vi c e s a nd r e s our c e s i n a dyna mi c f a s hi on t ha t be s t me e t s t he us e r ' s ne e ds a nd pr e f e r e nc e s [ 4] .…”