We introduce the Regular Language-Constrained Team Orienteering Problem with Time Windows (RLC-TOPTW) as a generalization of the Team Orienteering Problem with Time Windows (TOPTW). The problem is pertinent to application domains which entail categorization of graph/network nodes and constraints associated with the categories of the nodes in the solution path. RLC-TOPTW captures any type of constraints as long as they can be described by regular expressions, and its solution provides a feasible path that satisfies the constraints. As RLC-TOPTW is NP-hard we present two efficient heuristic approaches: The first heuristic is based on the solution approach for solving the Regular Language-Constrained Orienteering Problem with Time Windows (RLC-OPTW) given in[1] while the second is a genetic algorithm approach. The proposed algorithms have been assessed using publicly available datasets.

Abstract Face‐to‐face communication relies extensively on non‐verbal cues (NVCs) which complement, or at times dominate, the communicative process as they convey emotions with intense salience, thus definitively affecting interpersonal communication. The capture, transference, and subsequent interpretation of NVCs becomes complicated in computer‐mediated communicative processes, particularly in shared virtual worlds, for which there is growing interest both in regard to NVCs technological integration and their affective impact. This paper presents a between‐groups experimental setup which is facilitated in immersive virtual reality (IVR), and examines NVCs effects on user experience, with special emphasis on degree of attention toward each NVC as an isolated controlled variable of a scripted performance by a virtual character (VC). This study aims to evaluate NVCs fidelity based on the capabilities of the motion‐capture technologies utilized to address cue integration developmental challenges and examines NVCs impact on users' perceived realism of the VC, their empathy toward him, and the degree of social presence experienced. To meet the objectives set the affective impact of low‐fidelity automated NVCs and high‐fidelity real‐time captured NVCs were compared. The findings of the evaluation suggest that although NVCs do impact user experience to an extent, their effects are notably more subtle compared to previous studies.

This paper addresses the problem of operator-based vehicle repositioning in free-floating electric car-sharing systems (FFCSs). New algorithmic techniques are developed which derive cost-effective relocation tours by primarily minimizing relocation drivers' walking time. Car repositioning takes place overnight and aims at complete rebalancing of the system i.e., at achieving an optimal, based on user demand, cars distribution among nonoverlapping cells of the FFCS's operating area. The battery level of the electric cars is also taken into account when deciding if and where each car will be relocated. If k is the number of employees handling car relocations from oversupplied to undersupplied regions, when k = 1 i.e., there exists a single employee carrying out a relocation tour comprising alternating phases of a car relocation followed by walking to the next to be relocated car, we define and solve the Minimum Walking Car Repositioning Problem (MWCRP) whose main objective is to minimize the walking distance in the relocation tour as the walking part of such a tour is tiresome and takes more time than the driving one. We also define and solve the k-MWCRP when k > 1 to handle the case that a team of more than one drivers is employed to take on the relocation plan. It is worth mentioning that these are the first vehicle relocation techniques lowering the relocation cost by mostly minimizing the walking cost. Performance results confirm the effectiveness of the proposed algorithms.

Social psychology has been shedding light for decades to the complexities of interpersonal communication, whilst other fields, such as Computer-mediated Communication, showcase how mediums of communication affect interlocutors to re-negotiate symbolic interactionism. Current developments in Virtual Reality (VR), with the emergence of Social VR among others, compel for a close examination of VR-mediated communication and the probable effects it might have on communicative processes. In this study we conducted an explorative, between-groups comparative experiment, with 51 participants, to establish how susceptible they are to techniques of persuasion and authority when those are filtered through a synthetic environment. As this was an uncharted area of inquiry, our only hypothesis was in reference to level of realness, based on which, face-to-face interactions posed greater probability of participant compliance. Our main findings refute this hypothesis, since the second group (VR) was substantially more susceptible to persuasion techniques.

Mobile Context-Aware Recommender Systems (CARS) have recently emerged aiming at generating recommendations relevant to the specific environmental and situational usage context. This article reports on the design and implementation of a collaborative filtering-based mobile CARS, developed as part of an e-platform that supports location-based search for retail products and services sold by nearby physical retailer shops. In addition to the current user location, our RS considers a multitude of contextual factors like time, season, demographic data, consumer behavior, and location history of the user in order to derive more meaningful product recommendations. The RS has been tested on real operational environments as well as on lab evaluation trials demonstrating higher accuracy and relevance of recommendations against two baseline approaches.

Providing efficient, sustainable and personalized mobility services in urban environments that combine a spectrum of transport modes (e.g., public transport, electric vehicles, vehicle sharing, low energy and/or emission routes) constitutes a great challenge. In this work, we present MOVESMART, a holistic approach (and integrated platform) for the provision of renewable personal mobility services, leveraging crowd-sourcing data, tools for collecting real-time information by multimodal travelers, and traffic prediction mechanisms. MOVESMART guarantees real-time responses to renewable (on-demand) mobility queries for efficient multi-modal route planning that are time-dependent as well as sensitive to aperiodic incidents and traffic prediction forecasts. This paper focuses on the cloudbased (backend) services of the MOVESMART platform.

The various problems regularly encountered in urban residential environments can have significant impact on citizen's quality of life, while simultaneously their identification, reporting and management by the responsible authorities entail a very demanding process. Providing citizens with mobile applications for participatory reporting (i.e. crowdsourcing) of problems may help streamline the work of relevant municipal services; such citizen-centric services will make the city smarter through enhanced problem management and request processing. In this article, we introduce two new mobile applications, CityCare and CityCareW, which are complementary with respect to each other and cover all phases of a problem report lifecycle. They incorporate innovative mechanisms that allow the detection of the most critical problems, as well as duplicate problem reports while gamification mechanisms are applied to motivate citizen participation. Trial evaluations have shown that the two applications are user-friendly and satisfy their end-users to a very considerable extent.

Mobility of people and goods in urban environments raises several quality and sustainability concerns. While ICTs have established the ground for developing intelligent transport services, their effective use for supporting cleaner urban mobility still represents a major research challenge. The eCOMPASS research project addressed this challenge through introducing new mobility concepts and establishing a methodological framework for route planning optimization, delivering a comprehensive set of innovative tools and services for end-users to enable eco-awareness in urban transport. eCOMPASS innovative tools are based on new algorithmic technology concerning tools and methods for vehicle routing (cars and vehicle fleets) and multimodal human mobility for city dwellers and tourists. eCOMPASS involved a generic architecture that considered all types and scenarios of human and goods mobility in urban environments minimizing their environmental impact. In this work, we report on the main scientific innovations and end-products of eCOMPASS for vehicle routing, including car route planning and vehicle fleets.

The environmental impact of the steadily increasing demand for mobility of people and goods, especially in urban environments, raises public concern and presents challenges that need to be addressed in the interest of long-term sustainability. Along this line, the inherently eco-friendly human mobility which involves the use of urban public transit networks must be encouraged and eased. This necessitates the development of context-aware services that hide the complexity of public transit networks while considering all available transportation modalities (e.g. bus, metro, tram, walking and cycling) in order to provide sophisticated route planning tailored to both residents and visitors of urban areas. The EU-funded eCOMPASS research project has addressed this challenge through establishing a methodological framework for route planning optimization. A core objective of the project has been to employ novel algorithm engineering approaches for delivering a comprehensive set of tools and services (accessible from web/mobile application interfaces) for mobile end users to enable eco-awareness in urban multi-modal transfers. eCOMPASS delivered web and mobile services providing multimodal public transportation route planning, considering contextual information as well as various restrictions and/or user constraints. Herein, we report the motivation, main scientific innovations and present the end-products of eCOMPASS with respect to multimodal human mobility.

The recent release of affordable head mounted displays (HMDs) foretells a near future where a variety of social interactions could be taking place in VR environments. There is little knowledge however as to how actual social conditions impact users during a virtual experience. We investigate this issue by placing 54 individuals into a virtual clothing store and having them witness the exposure of their avatar's naked virtual body, being either alone or in the presence of a virtual salesman. Our results indicate that a second character does not affect levels of presence and body ownership illusion, but does cause a strong emotional response, thus suggesting that social context and social presence affectively impact users.

The recent developments in the area of mobile technologies have enabled the diffusion of augmented reality. This article explores new possibilities for leveraging the power of augmented reality, further to its typical use as a means for projecting virtual content over physical objects. That is, it investigates the potential of augmented reality as a tool for participatory content creation and sharing. In order to demonstrate this idea, we have developed Flaneur, a mobile augmented reality application which invites users to wander around a city to discover and highlight its architectural assets. Flaneur serves both as an architectural heritage guide and as a crowdsourcing platform. In particular, further to consuming content edited by administrators, users are enabled to share their knowledge and experiences about heritage buildings through uploading textual and graphical annotation, which is later delivered to peer users as augmented context. The platform allows the documentation of architecture-relevant content either for whole building blocks or even for specific architectural and decorative elements. Moreover, it enables the precise placement and arrangement of digital content over the physical asset to be augmented. Flaneur has been evaluated though field trials, which provided valuable insights as regards the effectiveness, utility and restrictions of the application.

Guest Editorial.

Several mobile guides for unknown destinations provide assistance to tourists (through personalized tour recommendations) in making feasible plans and visiting the most interesting POIs within their available time. However, existing tourist tour planners only regard available attractions as sites lacking physical dimensions (i.e. POIs are treated as points). Although this is adequate for scheduling visits at POIs with single entry/exit points, it fails to capture practical properties of typical tourist visiting styles in urban destinations (e.g. tourists typically enjoy walking on pedestrian zones, market areas and scenic neighborhoods). Herein, we introduce Scenic Athens, a context-aware mobile city guide for Athens (Greece) which delivers personalized tour planning services to tourists deriving near-optimal sequencing of POIs along recommended tours. Scenic Athens takes into account a multitude of travel restrictions and POI properties, also incorporating scenic (walking) routes (in addition to point POIs), thereby supporting more experiential exploration of tourist destinations. A user evaluation study validated the recommendation value, usability and perceived utility of the proposed application.

Pervasive games integrate physical and social aspects of the real world into a unified gaming experience, where virtual and physical game elements co-exist. The blending of game content with the context of the physical environment has been recognized as an important element that increases the enjoyment, interest and engagement of players in in this game genre. To address this requirement most pervasive games prototypes so far have been bound to specific locations, being heavily dependent on orchestration teams to edit game content and support the overall game execution. However, the capacity of pervasive games to be staged anywhere (i.e. their portability) is critical for their wider adoption and commercial success. Since the manual editing of game content by game developers is clearly incompatible with portability, User-Generated Content (UGC) remains as the only practical option for content provision in pervasive games. Nevertheless, the impact of UGC has not been investigated so far in the pervasive games literature. This article introduces Barbarossa, a pervasive role-playing game incorporating UGC as a means for game content generation. The user trials of Barbarossa confirmed that the use of UGC can enhance the quality of experience perceived by players. We also document good practices with respect to the effective incorporation of UGC in pervasive games, which could be useful to future developers.

The investigation of mobile agent (MA) middleware as a technology for implementing efficient data fusion schemes on wireless sensor networks (WSN) has been a subject of intense research in the past few years. Nevertheless, the itineraries followed by travelling MAs largely determine the overall performance of the data fusion applications. Along this line, this article introduces a novel algorithmic approach for efficient itinerary planning of MA objects engaged in data fusion tasks. Our algorithm adopts an iterated local search (ILS) approach in deriving the hop sequence of multiple travelling MAs over the deployed source nodes. Simulation results demonstrate the performance gain of our method against existing multiple MA itinerary planning methods.

A critical issue dealt with in Wireless Sensor and Actor Networks (WSANs) is the real time response of actors to events occurring in the network area. The fast notification of actors from Sensor Nodes (SNs) about the events as well as the effective coordination of actors for prompt event handling is most important in these networks. In this paper, we introduce a distributed protocol for effective event handling in a WSAN. Existing approaches mainly favoring actors near the current event for handling it, may lead to highly ineffective solutions for certain worst-case scenarios. Through a randomized approach, our solution also selects distant actors for handling events, and guarantees fast average responsiveness to events and a balanced energy distribution among actors. In addition, it features efficient distributed algorithms for sensor to actor and actor to actor coordination which are of independent interest.

Tourists become increasingly dependent on mobile city guides to locate tourist services and retrieve information about nearby points of interest (POIs) when visiting unknown destinations. Although several city guides support the provision of personalized tour recommendations to assist tourists visiting the most interesting attractions, existing tour planners only consider walking tours. Herein, we introduce eCOMPASS, a context-aware mobile application which also considers the option of using public transit for moving around. Far beyond than just providing navigational aid, eCOMPASS incorporates multimodality (i.e. time dependency) within its routing logic aiming at deriving near-optimal sequencing of POIs along recommended tours so as to best utilize time available for sightseeing and minimize waiting time at transit stops. Further advancing the state of the art, eCOMPASS allows users to define arbitrary start/end locations (e.g. the current location of a mobile user) rather than choosing among a fixed set of locations. This paper describes the routing algorithm which comprises the core functionality of eCOMPASS and discusses the implementation details of the mobile application using the metropolitan area of Berlin (Germany) as case study.

Pervasive games represent an exciting development in gaming which leverages the use of sensor, visualization and networking technologies to provide immerse live-action game experiences. The field of pervasive games has been intensively researched in the recent years, as evidenced from the proliferation of available prototypes. Existing pervasive game projects commonly do not enable relocation of the game space while also overlooking several aspects which critically affect user acceptance and game experience such as scenario design, usability of employed technologies, game duration and intensity. This article introduces Barbarossa, an outdoor pervasive role-playing game. Barbarossa addresses the abovementioned issues featuring several portable game modes. It also takes into account concrete technology usage requirements for each game mode according to the game session duration and player effort required. Further, game experience is enhanced through incorporating several contextual parameters. User evaluation trials indicated warm reception of Barbarossa by players and confirmed that the main game design objectives have been largely achieved.

This article presents a novel crawling and clustering method for extracting and processing cultural data from the web in a fully automated fashion. Our architecture relies upon a focused web crawler to download web documents relevant to culture. The focused crawler is a web crawler that searches and processes only those web pages that are relevant to a particular topic. After downloading the pages, we extract from each document a number of words for each thematic cultural area, filtering the documents with non-cultural content; we then create multidimensional document vectors comprising the most frequent cultural term occurrences. We calculate the dissimilarity between the cultural-related document vectors and for each cultural theme, we use cluster analysis to partition the documents into a number of clusters. Our approach is validated via a proof-of-concept application which analyzes hundreds of web pages spanning different cultural thematic areas.

A large class of Wireless Sensor Networks (WSN) applications involve a set of isolated urban areas (e.g., urban parks or building blocks) covered by sensor nodes (SNs) monitoring environmental parameters. Mobile sinks (MSs) mounted upon urban vehicles with fixed trajectories (e.g., buses) provide the ideal infrastructure to effectively retrieve sensory data from such isolated WSN fields. Existing approaches involve either single-hop transfer of data from SNs that lie within the MS's range or heavy involvement of network periphery nodes in data retrieval, processing, buffering, and delivering tasks. These nodes run the risk of rapid energy exhaustion resulting in loss of network connectivity and decreased network lifetime. Our proposed protocol aims at minimizing the overall network overhead and energy expenditure associated with the multihop data retrieval process while also ensuring balanced energy consumption among SNs and prolonged network lifetime. This is achieved through building cluster structures consisted of member nodes that route their measured data to their assigned cluster head (CH). CHs perform data filtering upon raw data exploiting potential spatial-temporal data redundancy and forward the filtered information to appropriate end nodes with sufficient residual energy, located in proximity to the MS's trajectory. Simulation results confirm the effectiveness of our approach against as well as its performance gain over alternative methods.

This paper deals with the problem of deriving personalized recommendations for daily sightseeing itineraries for tourists visiting any destination. Our approach considers selected places of interest that a traveler would potentially wish to visit and derives a near-optimal itinerary for each day of visit; the places of potential interest are selected based on stated or implied user preferences. Our method enables the planning of customized daily personalized tourist itineraries considering user preferences, time available for visiting sights in daily basis, opening days of sights and average visiting times for these sights. Herein, we propose a heuristic solution to this problem and discuss its implementation aspects.

Damianos Gavalas, Grammati Pantziou, Charalampos Konstantopoulos; Mobility in Wireless Sensor Networks, The Computer Journal, Volume 54, Issue 12, 1 November 20

Mobile tourist guides have been in the spotlight during the past decade resulting in many prototypes, either full-fledged standalone mobile applications or web-based applications. Particular emphasis has been given to personalisation of services, typically based on travel recommender systems used to assist tourists in choosing places to visit; these systems address an important aspect of personalization and hence reduce the information burden for the user. However, existing systems fail to exploit information, behaviors, ideas, evaluations, assessments, ratings, etc, by other tourists with similar interests, which provide ground for the cooperative production of tourist content and travel recommendations. In this paper we extend this notion of travel recommender systems utilizing collaborative filtering techniques for deriving improved recommendations. We also propose the use of Wireless Sensor Network (WSN) installations around tourist sites for providing mobile users convenient and inexpensive means for uploading tourist information and ratings about Points of Interest (POI) via their mobile devices. User ratings uploaded through WSN infrastructures are weighted higher to differentiate between users that rate POIs using the mobile tourist guide application in direct proximity of the POI and others using the Internet away from the POI.

This short paper deals with the problem of deriving personalized recommendations for daily sightseeing itineraries for tourists visiting any destination. Our approach considers selected places of interest that a traveller would potentially wish to visit and derives a near-optimal itinerary for each day of visit; the places of potential interest are selected based on stated or implied user preferences. Herein, we propose a heuristic solution to this problem and discuss its implementation aspects.

A key feature of wireless sensor networks (WSNs) is the collaborative processing, where the correlation existing over the local data of sensor nodes (SNs) is exploited so that the total data volume can be reduced (data aggregation). The use of Mobile Agents (MAs), i.e., software entities able of migrating among nodes and resuming execution naturally, fits in this scenario; the local data of an SN can be combined with the data collected by an MA from other SNs in a way that depends on the specific program code of the MA. In this paper, we consider the problem of calculating near-optimal routes for MAs that incrementally aggregate the data as they visit the nodes in a distributed sensor network. Our algorithm follows a greedy-like approach always selecting the next node to be included in an itinerary in such a way that the cost of the so far formed itineraries is kept minimum at each step. Simulation results confirm the high effectiveness of the proposed algorithm as well as its performance gain over alternative approaches. Also, with the use of proper data structures, the computational complexity of the algorithm is kept low as it is formally proved in the paper.

Abstract Jamming is defined as the act of intentionally directing electromagnetic energy towards a communication system to disrupt or prevent signal transmission. In the context of wireless sensor networks (WSNs), jamming is the type of attack which interferes with the radio frequencies used by sensor nodes and may be viewed as a special case of denial of service (DoS) attacks. Herein, we outline the possible jamming attacks a WSN may encounter. The main contribution of this paper is the outline of the design specifications of a prototype node ‘Ares’ that effectively defends jamming attacks. Our focus is on frequency hopping spread spectrum (FHSS) and direct sequence spread spectrum (DSSS), two of the most effective countermeasures against jamming. The main novel aspect of Ares is that it uses a hybrid FHSS–DSSS approach to defend jamming attacks. We suggest the use of a specific FHSS technique in 5 GHz band with 51 frequency channels wherein the channel sequence is generated using a key (which derives from a secret word), known only to the sink and the sensor nodes, as a seed. Each channel uses DSSS modulation with 16‐bit pseudo noise (PN) code. The PN code derives from the same key used for FHSS channel generation. The pre‐eminence of our method against alternative anti‐jamming techniques is demonstrated through extensive simulation tests. Copyright © 2008 John Wiley & Sons, Ltd.

Mobile agents (MAs) have been initially developed to replace the client/server model which shows many disadvantages in WSN environments (e.g. very high bandwidth and energy utilization). Herein, we present CBID (Clone-Based Itinerary Design), a novel algorithm that calculates near-optimal routes for MAs that incrementally fuse the data as they visit the nodes while enabling a fast update of designed itineraries which is especially important for highly dynamic topologies. The order of visited nodes highly affects the quality and the overall cost of data fusion. The key MAs characteristic exploited by CBID to reduce energy consumption and response time is their cloning capability. Parallel dispatched MAs sequentially visit sensor nodes arranged in tree structures and upon visiting a node with two or more child nodes, the MAs (master MAs) clone of themselves with each clone (slave MA) visiting a tree branch. When all slave MAs return to that node, report their data to the master MA and are self-destroyed. This results in highly reduced energy consumption and response time since many MAs work in parallel. Simulation results prove the high effectiveness of CBID in data fusion tasks compared to other alternative algorithms.

In this article, we consider the problem of calculating an appropriate number of near-optimal (subject to a certain routing objective) routes for mobile agents (MAs) that incrementally fuse the data as they visit the nodes in a distributed sensor network. We propose an improved heuristic algorithm which computes an approximate solution to the problem by suggesting an appropriate number of MAs and constructing near-optimal itineraries for each of them. The performance gain of our algorithm over alternative approaches both in terms of cost and task completion latency is demonstrated by a quantitative evaluation and also in simulated environments through a Java-based tool.

Wireless sensor networks (WSNs) are used in many applications which often include the monitoring and recording of sensitive information. Hence, their critical importance raises many security concerns. In the context of WSNs, jamming is the type of attack which interferes with the radio frequencies used by network nodes. In the event that an attacker uses a rather powerful jamming source, disruptions of WSNs proper function are likely to occur. As a result, the use of countermeasures against jamming in WSN environments is of immense importance. The main contribution of this article is the discussion of various defence methods against jamming that would allow a WSN to survive and work properly in a hostile jamming environment. Our focus is on frequency hopping spread spectrum (FHSS) and direct sequence spread spectrum (DSSS), two of the most effective countermeasures against jamming. We suggest the use of a specific FHSS technique in 5 GHz band with 55 frequency channels wherein the channel sequence is generated using a secret word, known only to the sink and the sensor nodes, as a seed. Each channel uses DSSS modulation with 16 bit Pseudo Noise (PN) code, which derives from the same secret word used for FHSS channel generation.

Organization, scalability and routing have been identified as key problems hindering viability and commercial success of mobile ad hoc networks. Clustering of mobile nodes among separate domains has been proposed as an efficient approach to address those issues. In this work, we introduce an efficient distributed clustering algorithm that uses both location and energy metrics for cluster formation. Our proposed solution mainly addresses cluster stability, manageability and energy efficiency issues. Also, unlike existing active clustering methods, our algorithm relieves the network from the unnecessary burden of control messages broadcasting, especially for relatively static network topologies. This is achieved through adapting broadcast period according to mobile nodes mobility pattern. The efficiency, scalability and competence of our algorithm against alternative approaches have been demonstrated through simulation results.

Proposed management architectures, incorporating mobile agent (MA) technology, fail to address scalability problems, when monitoring tasks employing multi-hop agents are considered. This is because they lack mechanisms, which can guarantee that the agents itinerary is optimised so as to minimise migration traffic and round-trip latency. Herein, we propose an algorithm that adapts methods usually applied for addressing network design problems in the problematic of MA itinerary planning. The algorithm not only suggests the optimal number of MAs that minimise the overall cost but also constructs optimal itineraries for each of them. The algorithm implementation has been integrated into our MA framework research prototype while its validity and competence has been verified through simulation results over large enterprise networks.

The emphasis of research projects in the field of mobile agent (MA) technology has been mainly put on identifying applications where the employment of MAs is preferable compared to centralised or alternative distributed computing models. Very little has been done though on examining how MA platforms design could be optimised so as to minimise the network traffic and latency associated with MA transfers. The work presented herein addresses these issues by investigating the effect of several optimisation ideas applied on our MA platform prototype. Furthermore, we discuss the results of a set of timing experiments aimed at offering a better understanding of the agent migration process and suggesting ways for reducing MA transfer delays.

This paper introduces the concept of dynamic hierarchical management, enabled by mobile agent (MA) technology. The proposed framework addresses the scalability limitations of the centralised paradigm and the poor flexibility of static hierarchical management architectures to changing networking conditions. The increased adaptability of our framework is enabled by a novel management entity, termed mobile distributed manager (MDM), MDMs, being MAs themselves, can dynamically migrate to an assigned network domain (given that certain requirements are met) and undertake its management responsibility, operating at an intermediary level between the central manager and SNMP agents, localising the associated management traffic. The paper also focuses on the design decisions and implementation experiences of the proposed architecture.

The intrinsic scalability limitations of traditional centralised network management (NM) become significantly more pronounced when transfers of bulk network monitoring data are considered. This fact has encouraged a trend towards distributed management intelligence, which promises more flexible and scalable solutions. However, distributed mobile agent (MA) based NM architectures reported in the literature do not adequately address scalability problems when considering data-intensive NM applications. In this paper, we present three novel applications in which MA are used to perform management data aggregation, acquire SNMP table snapshots and filter SNMP table contents subject to filtering expressions. Both real-time and off-line NM data acquisition is considered. The applications, supported by a lightweight management framework described in previous work, are shown to outperform SNMP-based polling in terms of bandwidth consumption.

The use of mobile agent technology to distribute and delegate management tasks promises to overcome the scalability and flexibility limitations of the centralised network management paradigm. An efficient, lightweight infrastructure based on mobile agents is described, which addresses these issues by distributing management operations amongst managed devices and hence reduces the processing load and bandwidth usage. A mobile agent generator that facilitates the creation of new mobile agents for additional services is also presented. Our infrastructure is shown to outperform SNMP both in terms of the polling response time and bandwidth consumption when considering data intensive operations.

Distributed network management (NM) architectures exploiting the advantages of mobile agents (MA) promise to relieve some of the limitations intrinsic to client-server based centralised NM, such as lack of scalability, interoperability and flexibility. However, the use of MAs alone could impose an unnecessary transmission overhead if mobile code were to be used for trivial tasks. Hence, an infrastructure based on a hybridisation of centralised and distributed approaches is proposed, which maintains the lightweight nature of centralised NM for trivial management tasks, whilst adopting a distributed MA-based scheme as task complexity and suitability changes. Remote processing and compression of NM data issues are investigated in order to reduce the bandwidth usage. Security enhancements are also considered.