Hyper-responsive mobile applications, such as augmented reality and online games, require ultra-low latency access to back-end services and data at runtime. While fog computing tries to meet such latency requirements by placing corresponding back-end services and data closer to clients, for e.g., within an access network, assuming a fixed back-end server throughout execution is problematic due to user mobility. A more flexible approach is thus required to allow for adapting to changes in network conditions when users roam, by relocating back-end services and data to closer available infrastructure. Support for real-time migration of software services exists, however, migrating associated disk state remains a bottleneck. This paper presents FOGFS, a fog file system that employs intelligent snapshotting, migration and synchronization mechanisms to speed up the migration of an application`s disk state between different edge locations at runtime. The experimental evaluation of our prototype implementation reveals that the attainable speed-up is as much as 3. 3 × compared to conventional migration approaches.

No abstract available.

Graphical password composition is an important part of graphical user authentication which affects the strength of the chosen password. Considering that graphical authentication is associated with visual search, perception, and information retrieval, in this paper we report on an eye-tracking study (N = 109) that aimed to investigate the effects of users’ cognitive styles toward the strength of the created passwords and shed light into whether and how the visual strategy of the users during graphical password composition is associated with the passwords’ strength. For doing so, we adopted Witkin’s Field Dependence-Independence theory, which underpins individual differences in visual information and cognitive processing, as graphical password composition tasks are associated with visual search. The analysis revealed that users with different cognitive processing characteristics followed different patterns of visual behavior during password composition which affected the strength of the created passwords. The findings underpin the need of considering human-cognitive characteristics as a design factor in graphical password schemes. The paper concludes by discussing implications for improving recognition-based graphical passwords through adaptation and personalization techniques based on individual cognitive characteristics.

The uptake of wearable technology suggests that the time is ripe to explore new opportunities for improving mobile experiences. Apps, however, are not keeping up with the pace of technological advancement because wearables are treated as standalone devices, although their individual capabilities better classify them as peripherals with complementary roles. We foresee that the next generation of apps will orchestrate multiple wearable devices to enhance mobile user experiences. However, currently there is limited support for combining heterogeneous devices. This paper introduces Multi-Wear, a platform to scaffold the development of apps that span multiple wearables. It demonstrates experimentally how MULTI-WEAR can help bring changes to mobile apps that go beyond conventional practices.

Visual attention, search, processing and comprehension are important cognitive tasks during a graphical password composition activity. Aiming to shed light on whether individual differences on visual behavior affect the strength of the created passwords, we conducted an eye-tracking study (N=36), and adopted an accredited cognitive style theory to interpret the results. The analysis revealed that users with different cognitive styles followed different patterns of visual behavior which affected the strength of the created passwords. Motivated, by the results of the first study, we introduced adaptive characteristics to the user authentication mechanism, aiming to assist specific cognitive style user groups to create more secure passwords, and conducted a second study with a new sample (N=40) to test the adaptive characteristics. Results strengthen our assumptions that adaptive mechanisms based on users' differences in cognitive and visual behavior uncover a new perspective for improving the password's strength within graphical user authentication realms.

Evidence suggests that individual cognitive differences affect users' memorability, visual behavior, and graphical passwords' security. Such knowledge denotes the added value of personalizing graphical password schemes towards the unique cognitive characteristics of the users. However, real-time and accurate cognition-based predictive user models are necessary to reach such a breakthrough. In this paper, we present the results of such an attempt, where an in-lab eye-tracking study was conducted with 36 participants who completed a recall-based graphical password composition task. We adopted a credible cognitive style theory, and investigated a variety of eye-tracking metrics to predict participants' cognitive styles. Results' analysis reveals that inferring individual cognitive differences in real-time during graphical password composition is feasible within a few seconds and that specific eye-tracking metrics correlate stronger with certain cognitive style groups. The findings further support the vision of incorporating real-time adaptive mechanisms in graphical password schemes for the benefit of service providers and end-users.

Adaptive user authentication policies are moving in the center of attention lately aiming to assist users in creating memorable and secure passwords. Focusing on graphical user authentication, state-of-the-art research has provided evidence that image-related attributes affect password memorability and security. Nonetheless, the effects of users' contemporary cultural-related memories towards password memorability and security have not been investigated so far, although it is known that user authentication is a cross-cultural task. Aiming to shed light on whether such effects exist, we conducted a study in which users created a graphical password with a contemporary culture-intensive vs. a culture-neutral image. Results indicate that image content related to one's cultural-related memories affects the interaction behavior during password composition, and consequently password memorability. Findings point towards a promising new direction for considering human contemporary cultural memories in the design of adaptive password policies to increase memorability and preserve security.

Intelligent interactive systems should not ignore the individuality of the user. The "one-size-fits-all" approach, especially in user interaction, is not appropriate when user satisfaction and acceptability is a primary goal. Each user has unique human cognitive processing styles and abilities. In addition, emotions change over time, which possibly affect the user's cognitive state and the overall interaction process. Unsurprisingly, the users' ability to control their emotions is another essential factor in adapting user interfaces, applications and data delivery. How can an interactive system adapt to human cognitive and emotional factors with the aim to deliver a personalized and more usable interface? Is there a user interface to an application or system that is equally effective to all types of users? How can we place the human in the center of every day's interaction and task activity? This keynote speech will present some approaches that our work at the DMAC Lab/SCRAT Group has addressed on how individual differences in human cognitive processing and emotional factors place the user in the center of every day interaction.

Recent research provides evidence that individual differences in human cognitive styles affect user performance and experience in diverse application domains. However, state-of-the-art elicitation methods of cognitive styles require researchers to apply explicit, in-lab, and time-consuming "paper-and-pencil" techniques, rendering real-time integration of cognitive styles? elicitation impractical in interactive system design. Aiming to elaborate an implicit elicitation method of cognitive styles, this paper reports two feasibility studies based on an eye-tracking multifactorial model. In both studies, participants performed visual activities of varying characteristics, and the eye-tracking analysis revealed quantitative differences on visual behavior among individuals with different cognitive styles. Based on these differences, a series of classification experiments were conducted, and the results revealed that gaze-based implicit elicitation of cognitive styles in real-time is feasible, which could be used by interactive systems to adapt to the users' cognitive needs and preferences, to better assist them, and improve their performance and experience.

This paper investigates the trade-off between security and usability in recognition-based graphical authentication mechanisms. Through a user study (N=103) based on a real usage scenario, it draws insights about the security strength and memorability of a chosen password with respect to the amount of images presented to users during sign-up. In particular, it reveals the users' predisposition in following predictable patterns when selecting graphical passwords, and its effect on practical security strength. It also demonstrates that a "sweet-spot" exists between security and usability in graphical authentication approaches on the basis of adjusting accordingly the image grid size presented to users when creating passwords. The results of the study can be leveraged by researchers and practitioners engaged in designing intelligent graphical authentication user interfaces for striking an appropriate balance between security and usability.

Poor Internet performance currently undermines the efficiency of hyper-responsive mobile apps such as augmented reality clients and online games, which require low-latency access to real-time backend services. While edge-assisted execution, i.e. moving entire services to the edge of an access network, helps eliminate part of the communication overhead involved, this does not scale to the number of users that share an edge infrastructure. This is due to a mismatch between the scarce availability of resources in access networks and the aggregate demand for computational power from client applications. Instead, this paper proposes a hybrid edge-assisted deployment model in which only part of a service executes on LTE edge servers. We provide insights about the conditions that must hold for such a model to be effective by investigating in simulation different deployment and application scenarios. In particular, we show that using LTE edge servers with modest capabilities, performance can improve significantly as long as at most 50% of client requests are processed at the edge. Moreover, we argue that edge servers should be installed at the core of a mobile network, rather than the mobile base station: the difference in performance is negligible, whereas the latter choice entails high deployment costs. Finally, we verify that, for the proposed model, the impact of user mobility on TCP performance is low.

The proliferation of wearable and smartphone devices with embedded sensors has enabled researchers and engineers to study and understand user behavior at an extremely high fidelity, particularly for use in industries such as entertainment, health, and retail. However, identified user patterns are yet to be integrated into modern systems with immersive capabilities, such as VR systems, which still remain constrained by limited application interaction models exposed to developers. In this paper, we present Smart VR, a platform that allows developers to seamlessly incorporate user behavior into VR apps. We present the high-level architecture of Smart VR, and show how it facilitates communication, data acquisition, and context recognition between smart wearable devices and mediator systems (e.g., smartphones, tablets, PCs). We demonstrate Smart VR in the context of a VR app for retail stores to show how it can be used to substitute the requirement of cumbersome input devices (e.g., mouse, keyboard) with more natural means of user-app interaction (e.g., user gestures such as swiping and tapping) to improve user experience.

This demonstration paper presents a Web-based adaptive interactive system for personalizing the checkout process of M-Commerce Web environments, coined Persona Check. In particular, the system personalizes the visual and interaction design aspects of a mobile Web-based checkout process based on users' cognitive style theory which argues that individuals have differences in the way they process and organize information, as well as experience their context and environment in different manners and perspectives. The Persona Check system consists of three main components: i) an M-Commerce environment for creating and managing the checkout process designs, ii) a user modeling component in which explicit user data collection methods are performed for eliciting the users' cognitive processing characteristics, and iii) an adaptive user interface that is responsible for performing rule-based mechanisms for deciding and communicating the "best-fit" checkout process design to the users based on their cognitive styles.

An effective user authentication mechanism should embrace both security and usability aspects as its purpose is to ensure safety of operation of online services but as well usability and transparency to its end users. In an attempt to improve the usability and overall experience of user interactions during authentication, this paper proposes an alternative approach of personalizing user authentication tasks based on individual differences in cognitive processing. The presented approach is mainly driven by theories on individual differences in cognitive styles which argue that individuals recall and process textual and graphical information differently. In this realm, the paper presents a 4-month user study in which 153 participants interacted with a personalized user authentication mechanism in an ecological valid context. Analysis of results shows that the presented user authentication approach is a promising alternative to current state of user authentication practices.

Stimulated by a large number of different theories on human cognition, suggesting that individuals have different habitual approaches in retrieving, recalling, processing and storing verbal and graphical information, this paper investigates the effect of such processes with regard to user performance and preference toward two variations of knowledge-based authentication mechanisms. In particular, a text-based password authentication mechanism and a recognition-based graphical authentication mechanism were deployed in the frame of an ecological valid user study, to investigate the effect of specific cognitive factors of users toward efficiency, effectiveness and preference of authentication tasks. A total of 145 users participated during a five-month period between February and June 2012. This recent study provides interesting insights for the design and deployment of adaptive authentication mechanisms based on cognitive factors of users. The results and implications of this paper are valuable in understanding and modeling user interactions with regard to authentication mechanisms.

The bulk of social network applications for smart phones (e.g., Twitter, Face book, Foursquare, etc.) currently rely on centralized or cloud-like architectures in order to carry out their data sharing and searching tasks. Unfortunately, the given model introduces both data-disclosure concerns (e.g., disclosing all captured media to a central entity) and performance concerns (e.g., consuming precious smart phone battery and bandwidth during content uploads). In this paper, we present a novel framework, coined Smart Opt, for searching objects (e.g., images, videos, etc.) captured by the users in a mobile social community. Our framework, is founded on an in-situ data storage model, where captured objects remain local on their owner's smart phones and searches then take place over a novel lookup structure we compute dynamically, coined the Multi-Objective Query Routing Tree (MO-QRT). Our structure concurrently optimizes several conflicting objectives (i.e., it minimizes energy consumption, minimizes search delay and maximizes query recall), using a Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D) that calculates a diverse set of high quality non-dominated solutions in a single run. We assess our ideas with mobility patterns derived by Microsoft's Geolife project and social patterns derived by DBLP. Our study reveals that Smart Opt can yield query recall rates of 95%, with one order of magnitude less time and two orders of magnitude less energy than its competitors.

For many years people have been trying to measure differences between individuals. Over the course of time, a combination of developments in statistical know-how and the evolution of thought within psychology enabled the refinement of measures, and subsequently the assessment of more specific factors in the field of individual differences like different kinds of ability, affect and personality. This knowledge has been used in many areas within psychology and at the same time the advancement of technology has enabled the development of web-based appraisal systems that measure specific factors relevant to specific situations. This paper presents the theory behind a web-based assessment system and some first experimental results that will lead to the design of the web environment.

This paper presents the findings of a preliminary study about the use of bio-feedback sensors in the context of an educational hypermedia environment, skin conductance, blood volume pulse and heart rate physiological data were gathered. The aim of the study was to examine learners’ emotional arousal variability, and possible correlations of the physiological data with other psychological constructs such as trait and self-reported anxiety. Ten university students participated in two identical experiments, with a mixed between-within experimental design (20 samples). According to the findings, heart rate was significantly correlated with trait and self-reported state anxiety (in the second experiment), but not with academic performance in an on-line exam. Skin conductance and blood volume pulse had only marginal variations, perhaps due to the absence of intense stimuli.

Research on modelling affect and on interfaces adaptation based on affective factors has matured considerably over the past several years. Emotions are considered to play a central role in guiding and regulating learning, performance, behaviour and decision making, by modulating numerous cognitive and physiological activities. The basic objective of this paper is to analyse the way that individuals process their emotions and how they interact with other elements of their information-processing system. It will further underpin their significance taking into consideration the notion of emotion regulation, based on which users expect to receive the most apt personalized providerpsilas content. Special emphasis will be given in dispositional trait affect that serves as an overall estimation of an individualpsilas affective state and statistical evidence will be provided which suggest that affect can have both informational and processing effects on cognition.

Eye-tracking measurements may be used as a method of identifying userspsila actual behavior in a hypermedia setting. In this research, an eye-tracking experiment was conducted in order to validate the construct of cognitive style as a personalization parameter in adaptive e-Learning systems. The main research question was whether the verbalizer/imager axis of the cognitive style analysis theory reflects actual preferences in an e-learning environment and properly identifies learner types. The findings from a sample of 21 participants reveal statistically significant differences among types of learners; as hypothesized, imagers concentrate on visual content, verbalizers on text, while intermediates are placed in between.

This demo presents a graphical user interface and ranking system, coined KSpot, for effectively monitoring the K highest-ranked answers to a query Q in a wireless sensor network. KSpot deploys state-of-the-art distributed top-k query processing algorithms in order to realize both snapshot queries and historic queries minimizing the consumption of system resources and prolonging the lifetime of the deployed sensor network. Additionally, KSpot is user-friendly and customizable featuring an intuitive user interface that enables a user to express declarative SQL-like queries over any ad-hoc scenario and to display the results graphically as opposed to the traditional tabular representation. To demonstrate the applicability of our system during the conference, we will continuously identify the K conference rooms with the highest sound level and display them such that conference attendees will be able to quickly determine the rooms with the most active discussions. The demo will also allow attendees to customize the system by changing the target scenario (e.g., by adapting the K value, the sensed parameter, etc.) Finally, we will present KSpot's system panel which continuously displays the savings in energy and messages that our system yields.

Continuous queries in wireless sensor networks (WSNs) are founded on the premise of query routing tree structures (denoted as T), which provide sensors with a path to the querying node. Predominant data acquisition systems for WSNs construct such structures in an ad-hoc manner and therefore there is no guarantee that a given query workload will be distributed equally among all sensors. That leads to data collisions which represent a major source of energy waste. In this paper we present the energy-driven tree construction (ETC) algorithm, which balances the workload among nodes and minimizes data collisions, thus reducing energy consumption, during data acquisition in WSNs. We show through real micro-benchmarks on the CC2420 radio chip and trace-driven experimentation with real datasets from Intel Research and UC-Berkeley that ETC can provide significant energy reductions under a variety of conditions prolonging the longevity of a wireless sensor network.

This paper assumes a set of n mobile sensors that move in the Euclidean plane as a swarm. Our objectives are to explore a given geographic region by detecting spatio-temporal events of interest and to store these events in the network until the user requests them. Such a setting finds applications in mobile environments where the user (i.e., the sink) is infrequently within communication range from the field deployment. Our framework, coined SenseSwarm, dynamically partitions the sensing devices into perimeter and core nodes. Data acquisition is scheduled at the perimeter, in order to minimize energy consumption, while storage and replication takes place at the core nodes which are physically and logically shielded to threats and obstacles. To efficiently identify the nodes laying on the perimeter of the swarm we devise the Perimeter Algorithm (PA), an efficient distributed algorithm with a low communication complexity. For storage and fault-tolerance we devise the Data Replication Algorithm (DRA), a voting-based replication scheme that enables the exact retrieval of events from the network in cases of failures. Our trace-driven experimentation shows that our framework can offer significant energy reductions while maintaining high data availability rates. In particular, we found that when failures are less than 60% failure then we can recover over 80% of generated events exactly.

The research that is described in this paper focuses on incorporating theories of individual differences in information processing within the context of generic Hypertext and Hypermedia Environments. The main objective of this paper is to introduce a framework for the automatic reconstruction of Web content based on human factors. It is supported that human factors may be used in order to enhance the design of generic hypertext (or hypermedia) content in a measurable and meaningful way. A Web Browser extension set of custom xml tags has been therefore developed in order for the browser to recognize and implement these set of tags for the imminent transformation and enhancement of Web content. An increase on users’ satisfaction as well as more efficient information processing (both in terms of accuracy and task completion time), has been observed in the personalized condition than the original one. Consequently, it is supported that human factors may be used in order to enhance the design of generic hypertext (or hypermedia) content in a measurable and meaningful way.

Abstract. Challenges today in the Web personalization and adaptation research area are ranging not only to the heterogeneous user needs and user environment issues such as current location and time, but also on a number of other considerations with respect to multi-channel delivery of the applications concerning Web-based content related to services, educational multimedia, entertainment, commerce etc. Nowadays, most Web personalization systems implement various techniques to extract the user profiles, which serves as the main component of such systems, and based on given user preferences, navigation behaviour and the Web-based content returns the requested personalized result. The main scope of this paper is to present the various techniques employed by such systems with regards to user profiles extraction and introduce a comprehensive user profile, which includes User Perceptual Preference Characteristics. It further analyzes the main intrinsic users ’ characteristics like visual, cognitive, and emotional processing parameters incorporated as well as the “traditional ” user profile characteristics that together tend to give the most optimized, adapted and personalized outcome. It finally presents a Web adaptation and personalization system that implements the proposed comprehensive user profile as well as initial evaluation results.

Research on modelling affect and on interfaces adaptation based on affective factors has matured considerably over the past several years, so that designers of educational products are now considering the inclusion of components that take affect into account. Emotions are considered to play a central role in guiding and regulating behaviour by modulating numerous cognitive and physiological activities. This paper introduces a new model in the field of adaptive hypermedia, which integrates cognitive and emotional parameters and attempts to apply them on a web-based learning environment. Our purpose is to improve learning performance and, most importantly, to personalize web-content to userspsila needs and preferences, eradicating known difficulties that occur in traditional approaches. The specific article emphasizes on the emotional aspect of our model, since it presents results of our efforts to measure and include emotional processing parameters, by constructing a theory that addresses emotion and is feasible in Web-learning environments.

The use of atomic commit protocols in mobile ad-hoc networks involves difficulties in setting up reasonable time-outs for aborting a pending distributed transaction. This paper presents the non-blocking adjourn state, a concurrency control modification which makes time-outs in an atomic commit protocol for aborting a transaction unnecessary. Further, it enhances concurrency among transactions performing conflicting accesses to resources used by completed distributed transactions waiting for the commit protocol to be initiated.

Continuous queries in wireless sensor networks are established on the premise of a routing tree that provides each sensor with a path over which answers can be transmitted to the query processor. We found that these structures are sub- optimality constructed in predominant data acquisition systems leading to an enormous waste of energy. In this paper we present MicroPulse1, a workload-aware optimization algorithm for query routing trees in wireless sensor networks. Our algorithm is established on profiling recent data acquisition activity and on identifying the bottlenecks using an in-network execution of the critical path method. A node S utilizes this information in order to locally derive the time instance during which it should wake up, the interval during which it should deliver its workload and the workload increase tolerance of its parent node. We additionally provide an elaborate description of energy-conscious algorithms for disseminating and maintaining the critical path cost in a distributed manner. Our trace-driven experimentation with real sensor traces from Intel Research Berkeley shows that MicroPulse can reduce the data acquisition costs by many orders.

This paper presents a Web adaptation and personalization architecture that uses cognitive aspects as its core filtering element. The innovation of the proposed architecture focuses upon the creation of a comprehensive user profiling that combines parameters that analyze the most intrinsic users' characteristics like visual, cognitive, and emotional processing parameters as well as the "traditional" user profiling characteristics and together tend to give the most optimized adapted and personalized result to the user.

In this paper we introduce MINT (materialized in-network top-k) Views, a novel framework for optimizing the execution of continuous monitoring queries in sensor networks. A typical materialized view V maintains the complete results of a query Q in order to minimize the cost of future query executions. In a sensor network context, maintaining consistency between V and the underlying and distributed base relation R is very expensive in terms of communication. Thus, our approach focuses on a subset V(sube. V) that unveils only the k highest-ranked answers at the sink for some user defined parameter k. We additionally provide an elaborate description of energy-conscious algorithms for constructing, pruning and maintaining such recursively- defined in-network views. Our trace-driven experimentation with real datasets show that MINT offers significant energy reductions compared to other predominant data acquisition models.

In this paper we present MicroPulse, a novel framework for adapting the waking window of a sensing device S based on the data workload incurred by a query Q. Assuming a typical tree-based aggregation scenario, the waking window is defined as the time interval r during which S enables its transceiver in order to collect the results from its children. Minimizing the length of r enables S to conserve energy that can be used to prolong the longevity of the network and hence the quality of results. Our method is established on profiling recent data acquisition activity and on identifying the bottlenecks using an in-network execution of the Critical Path Method. We show through trace- driven experimentation with a real dataset that MicroPulse can reduce the energy cost of the waking window by three orders of magnitude.

Query by Browsing (QBB) is a relationally complete paradigm for creating Visual Query Language (VQL)s. It has been adapted successfully for use on handheld devices in the form of the Chiromancer interface, thus placing considerable search capabilities at the fingertips of mobile users. In this paper we describe an enhancement to the QBB paradigm to accommodate continuous queries through the use of active folders, i.e. folders whose contents are constantly updated. We thus demonstrate how such continuous queries coupled with a suitable context-describing database schema can be used to support a variety of context-aware application scenarios. A prototype architecture and context schema are described as are the extensions to the QBB paradigm and the additions to the Chiromancer interface needed to support these scenarios.

In this paper we introduce and formally define Query by Browsing (QBB), a scalable, relationally complete visual query language based on the desktop user interface paradigm and tuple relational calculus that allows the formulation of complex queries over relational, entity-relationship, object-oriented and XML data sources on a variety of handheld and desktop platforms. It is to our knowledge the first visual query language to combine the important characteristics of usability, scalability, expressive power and flexibility. We support these claims by demonstrating the similarity of the QBB paradigm to the popular desktop user interface paradigm, by relating it to relational calculus and relational algebra and by describing Chiromancer II, a Web-based implementation of the QBB paradigm for handheld devices. We also discuss ways in which non-relational sources can be represented and queried and compare QBB to related work in the area of visual query languages for a variety of data models. We finally offer conclusions and thoughts for future work.

In this paper, we consider semantic service discovery in a global computing environment. We propose creating a dynamic overlay network by grouping together semantically related services. Each such group of services is termed a community. Communities are organized in a global taxonomy whose nodes are related contextually. The taxonomy can be seen as an expandable distributed semantic index over the system services, which aims at improving service discovery. Our performance results indicate that in certain cases, our service discovery mechanism outperforms even the case in which service indexes are fully replicated at all system sites.

Mobile Agents have brought around a new way to perform computations and develop distributed application and it is now struggling for a visible position in the area of distributed and wireless computing. This panel explores the issues that affect and direct the acceptance or not of this computing paradigm, i.e., mobile agents technologies.

The Wireless environment requires new type of services and new ways for structuring the needed content. Personalization comes into aid via the creation of personalized portals that directly tones down factors that break up the functionally of the Internet/wireless services when viewed through wireless devices; factors like the “click count”, user response time (the “choice ” factor) and the size of the wireless network traffic. In this demo we present a flexible personalization system tuned for the wireless Internet taking into consideration user mobility and not only the user profile but the device profile as well. We demonstrate appropriate, to the wireless environment, metrics and our initial performance evaluation, using a real content provider’s content, indicates improvement ranging from 33 % to, for certain metrics, 60%. 1.

The View Generator (VG) is a system that provides the necessary components for the definition, materialization, storage, maintenance and re-use of views over remote Web-accessible databases. Through the system, clients identify Web databases of interest, access their metadata and create personalized views that can be shared by other clients. Creating personalized views provides a more efficient way of data processing than directly issuing complex queries to the data sources especially in the case of lightweight and wireless clients that suffer from scarce local resources, limited bandwidth and high communication costs. VG's multi-tier architecture implemented using mobile Java agents allows automatic code deployment as well as dynamic relocation of views.

Given the undeniable popularity of the Web, providing efficient and secure access to remote databases using a Web browser is crucial for the emerging cooperative information systems and applications. In this paper, we evaluate all currently available Java-based approaches that support persistent connections between Web clients and database servers. These approaches include Java applets, Java Sockets, Servlets, Remote Method Invocation, CORBA, and mobile agents technology. Our comparison is along the dimensions of performance and programmability. Our findings point out that best performance is not always achievable with high programmability and low resource requirements. Moreover, the mobile agent technology needs to improve its programmability while giving particular emphasis on its infrastructure.

In current distributed systems, the notion of mobility is emerging in many forms and applications. Mobility arises naturally in wireless computing since the location of users changes as they move. Besides mobility in wireless computing, software mobile agents are another popular form of moving objects. Locating objects, i.e., identifying their current location, is central to mobile computing. We present a comprehensive survey of the various approaches to the problem of storing, querying, and updating the location of objects in mobile computing. The fundamental techniques underlying the proposed approaches are identified, analyzed, and classified along various dimensions.

The popularity of the Web as a universal access mechanism for network information has created the need for developing Web-based DBMS client/server applications. However, the current commercial applet-based approaches for accessing database systems offer limited flexibility, scalability, and robustness. We propose a new framework for Web-based distributed access to database systems based on Java-based mobile agents. The framework supports lightweight, portable, and autonomous clients as well as operation on slow or expensive networks. The implementation of the framework using the aglet workbench shows that its performance is comparable to, and in some case outperforms, the current approach. In fact, in wireless and dial-up environments and for average size transactions, a client/agent/server adaptation of the framework provides a performance improvement of approximately a factor of ten. For the fixed network, the gains are about 40 percent and 30 percent, respectively. We expect our framework to perform even better when deployed using different implementation platforms as indicated by our preliminary results from an implementation based on Voyager.

The popularity of the Web as a universal access mechanism for network information has created the need for developing Web based DBMS client/server applications. However, the current commercial applet based methodologies for accessing database systems offer limited flexibility, scalability and robustness. We propose a new framework for Web based distributed access to database systems based on Java based mobile agents. The framework supports lightweight, portable and autonomous clients as well as operation on slow or expensive networks. The implementation of the framework shows that its performance is comparable to, and in some cases outperforms, the current approach. In fact, in wireless and dial-up environments and for average size transactions, a client/agent/server adaptation of the framework provides a performance improvement of approximately a factor of ten. For the fixed network, the gains are about 40% and 30% respectively.

Due to the wide range of services being supported, telecommunications networks are loaded with massive quantities of information. This stimulates extra concern for network survivability. In this paper, we use graph theoretic techniques for addressing network survivability issues by transforming the original network topology onto a trellis graph, which allows the application of computationally efficient methods to find disjoint routing paths. We investigate the time complexity of the new algorithm as well as the time complexity of another algorithm on trellis transformations, presented in our previous work. The two algorithms are compared and evaluated in terms of their time complexity. Conclusions on their performance are drawn which show that the new algorithm has a better performance by a factor of n, where n is the number of nodes in the network.

An emerging paradigm that handles multiple locii of control in a system allows multiple program threads to work on the same task, each thread to work on a different task, or a thread to work on multiple tasks for greater design flexibility or due to system constraints such as real-time demands and a high load on tasking. We use the definition of context to capture the notion of logical locus of control. The context of the work being currently executed must be identifiable uniquely by the application, the Resource Managers and the Transaction Manager because each context represents different work. In this paper we define context management by defining a local Context Manager and its user interface. We then show why the notion of context is required to solve the problems that arise in local and distributed transaction processing due to the emerging paradigm. We present solutions to these problems in transaction processing using the proposed context management.

Eleven two-phase commit (2PC) protocol variations that optimize towards the normal case are described and compared with a baseline 2PC protocol. Environments in which they are most effective are discussed. The variations are compared and contrasted in terms of number of message flows, number of log writes (both forced and non-forced), probability of heuristic damage, how damage is reported, and other tradeoffs.>

Entities such as mechanical assemblies are recursive when they contain other assemblies at a lower level of detail. In this paper we show how recursive CAD entities can be manipulated using an extended projection function. The new function finds nested sub-entities within entities that are modeled as trees of aggregations and generalizations. It allows these sub-entities to be found using expressions that are independent of the complexity of an entity's data structure. We describe the new function, its relationship to the transitive closure function, and its implementation in a CAD database system.