Pervasive Environments Research Articles

A Robust Reputation-Based Computational Model for Trust Establishment in Pervasive Systems

Distributed systems built in open competitive and highly dynamic pervasive environments are composed of autonomous entities that act and interact in an intelligent and flexible manner so as to achieve their own goals and aims. System entities may be classified into two main categories that are, in principle, in conflict. These are the service resource requestors (SRRs) wishing to use services and/or exploit resources offered by the other system entities and the service resource providers (SRPs) that offer the services/resources requested. Seeking for the maximization of their welfare, entities may misbehave, thus leading to a significant deterioration of system's performance. The scope of this paper is to present a computational model for trust establishment based on a reputation mechanism, which incorporates direct SRRs' experiences and information disseminated from witness SRRs on the basis of their past experiences with SRPs. The designed mechanism discriminates between unfair feedback ratings intentionally and unintentionally provided, takes into consideration potential changes to providers' behavior, and weighs more recent events in the evaluation of the overall reputation ratings. The proposed model has been extensively evaluated through simulation experiments. It exhibits good performance, as the reputation computation error introduced due to false feedback provision decreases significantly.

Context analysis approach for context aware applications deployed on pervasive environments

Software deployment is executed according a deployment architecture which describes the allocation of software components to its hardware hosts. In this paper, we tackle the issue of constructing correct deployment architectures for large distributed systems. Actually, such architectures should satisfy various constraints related to the software components and the target environment such as the hierarchical description of components , their connections and the resource constraints. We present a formal method for constructing deployment architectures using a formal language called BRS (Bigraphical Reactive System). This method provides a correct by design approach based on multi-scale modeling ensuring the correctness of the obtained deployment architectures. Following our approach, the designer starts by modeling the first scale architecture which is refined automatically by successively adding smaller scale components until obtaining the last scale deployment architecture.

Service discovery and prediction on Pervasive Information System

Recent evolution of technology and its usages, such as Bring Your Own Device and Internet of Things, transformed the way we interact with Information Systems , leading to a new generation of IS, called the Pervasive Information Systems. These systems have to face heterogeneous pervasive environments and hide the complexity of such environment end-user. In order to reach transparency and proactivity necessary for successful PIS, new discovery and prediction mechanisms are necessary. In this paper, we present a new user-centric approach for PIS and propose new service discovery and prediction based on both user’s context and intentions. Intentions allow focusing on goals user wants to satisfy when requesting a service. Those intentions rise in a given context, which influence the service implementation. We propose a service discovery mechanism that observes user’s context and intention in order to offer him/her the most appropriate service satisfying her/his intention on the current context. We also propose a prediction mechanism that tries to anticipate user’s intentions considering the user’s history and the observed context. We evaluate both mechanisms and discuss advanced features future PIS will have to deal with.

A Static Code and Dynamic Data Attestation based Intrusion Detection System for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have applications typically in ubiquitous and pervasive environments that make ensuring the security therein critical. Despite deployment with utmost stringent security measures, the intrusions and the adversarial attacks like node compromise and node tampering cannot be prevented. Hence, there is a need for devising an intrusion detection and prevention system that can withstand the resource constraints and work feasibly within the same. One such intrusion detection technique is code attestation which is useful for verifying the program integrity of nodes in such networks. Our focus here is on software based remote code attestation. The static code attestation techniques published in the literature only check the integrity of the static code embedded within sensor nodes whereas the dynamic data attestation techniques check the structural integrity of dynamically created data. We believe that an integrated approach that uses both the static and dynamic code attestation techniques can leverage the effectiveness of an intrusion detection system. In this paper, we propose our integrated approach for countering attacks based on code attestation. As we demonstrate using our experimental simulation studies, with the marginal increase in memory and computational overhead, our approach ensures improved overall security. To the best of our knowledge ours is the first attempt in following such an approach.

Fair Trade Metaphor as a Control Privacy Method for Pervasive Environments: Concepts and Evaluation.

This paper presents a proof of concept from which the metaphor of “fair trade” is validated as an alternative to manage the private information of users. Our privacy solution deals with user's privacy as a tradable good for obtaining environmental services. Thus, users gain access to more valuable services as they share more personal information. This strategy, combined with optimistic access control and transaction registry mechanisms, enhances users' confidence in the system while encouraging them to share their information, with the consequent benefit for the community. The study results are promising considering the user responses regarding the usefulness, ease of use, information classification and perception of control with the mechanisms proposed by the metaphor.

Pervasive Location Management Using Genetic Algorithm

In mobile environment, mobility plays an important role i.e. without mobility there won’t be any transaction inmobile networks. A mobile user calls stir from anywhere on the network. To keep the mobile connected, the networks should keep track of the incoming mobile receptive system.Both network should be effective, efficient to identify the optimum path and faster to find the number of mobile users.This is called location management, which contains the above two things in an efficient and effective manner. Here location update means the process of tracking the mobile terminals and paging means to find the correct mobile terminals. The main aim of this paper is to compute the least location update cost in pervasive environment. Actually this paper is used to integrate the intelligence in mobile environment to identify the least location updation and paging cost. By use of this intelligence, the extraction of output and its level of accuracy are very high.Here intelligence is used to manage the location. Here we have proposed to implement the above two aspects by using various operators of genetic algorithm to solve the reporting cells planning problem because the solution space to be searched is huge and its popularity & robustness. And also the new version of mobility pattern is used to minimize the total cost and to balance the Location update and search Paging. In the new system one mobility pattern is maintained in each and every visited cell. If the number of pattern is increased then the movement weight is reduced and the updating cost and seeking cost is also reduced. Mobile terminals update their positions upon entering one of these reporting cells.In our previous paper, we have used network size of 4X4 for testing purpose and in conclusion, we have mentioned the 6X6 and 8X8 network size as future extension. In this paper we have implemented that extension work for number of generation are 500 and 1,000 for executing various existing algorithms like POFLA, UMP and MIPN. Comparatively the new system is better than any other existing system we have mentioned. The main drawback here is same time taken for first call and maintain less time for subsequent calls only.

HCI Model with Learning Mechanism for Cooperative Design in Pervasive Computing Environment

This paper presents a human-computer interaction model with a three layers learning mechanism in a pervasive environment. We begin with a discussion around a number of important issues related to human-computer interaction followed by a description of the architecture for a multi-agent cooperative design system for pervasive computing environment. We present our proposed three-layer HCI model and introduce the group formation algorithm, which is predicated on a dynamic sharing niche technology. Finally, we explore the cooperative reinforcement learning and fusion algorithms; the paper closes with concluding observations and a summary of the principal work and contributions of this paper.

Sensorless sensing with WiFi

Can WiFi signals be used for sensing purpose? The growing PHY layer capabilities of WiFi has made it possible to reuse WiFi signals for both communication and sensing. Sensing via WiFi would enable remote sensing without wearable sensors, simultaneous perception and data transmission without extra communication infrastructure, and contactless sensing in privacy-preserving mode. Due to the popularity of WiFi devices and the ubiquitous deployment of WiFi networks, WiFi-based sensing networks, if fully connected, would potentially rank as one of the world's largest wireless sensor networks. Yet the concept of wireless and sensorless sensing is not the simple combination of WiFi and radar. It seeks breakthroughs from dedicated radar systems, and aims to balance between low cost and high accuracy, to meet the rising demand for pervasive environment perception in everyday life. Despite increasing research interest, wireless sensing is still in its infancy. Through introductions on basic principles and working prototypes, we review the feasibilities and limitations of wireless, sensorless, and contactless sensing via WiFi. We envision this article as a brief primer on wireless sensing for interested readers to explore this open and largely unexplored field and create next-generation wireless and mobile computing applications.

OntoHealth: a system to process ontologies applied to health pervasive environment

In the last years, ontologies are being used in the development of pervasive computing applications. The pervasive computing has as one of its goals to facilitate interoperability between context sensitive applications and entities that may interact in that pervasive space. This paper presents OntoHealth: a system to process ontologies applied to health pervasive environment. The main idea is that a hospital could be seen as this pervasive environment, where someone, through ubiquitous computing, engages a range of computational devices and systems simultaneously, in the course of ordinary activities, and may not necessarily even be aware that they are doing so. With the proposed ontology and the tool for its processing, the medical tasks can be shared by all components of this pervasive environment.

Self-adaptive communication for collaborative mobile entities in ERCMS

Adaptation of communication is required for maintaining the connectivity and the quality of communication in group-wide collaborative activities. This becomes challenging to handle when considering mobile entities in a wireless environment, requiring responsiveness and availability of the communication system. We address these challenges in the context of the ROSACE project where mobile ground and flying robots have to collaborate with each other and with remote human and artificial actors to save and rescue in case of disasters such as forest fires. This paper aims to expose a communication component architecture allowing to manage a cooperative adaptation which is aware of the activity and resource context into pervasive environment. This allows providing the appropriate adaptation of the activity in response to evolutions of the activity requirements and the changes in relation with the communication resource constraints. In this paper, we present a simulation of a ROSACE use case. The results show how ROSACE entities collaborate to maintain the connectivity and to enhance the quality of communications.

Exploring a Context-based Network Access Control for Mobile Devices

Abstract Significant advancement in mobile devices coupled with high speed networks have shifted personal computing towards pervasive environments. Mobile devices currently offer many value-added applications and services such as emailing, messaging, navigation, social networking, finance, and entertainment. Typically, such value-added applications have access to users’ personal information and are capable of gathering and transmitting trust sensitive information, hence posing security risks and/or privacy concerns. In this paper, we propose a context-based analytic hierarchy process (AHP) framework for eliciting context information and adapting this information with network access control measures for mobile devices. The framework enforces the execution of mobile applications inside security incubators to control the communication between mobile applications and mobile device resources. Mobile applications’ access requests are analyzed based on user's context information collected from the mobile device sensors and the application network access control configuration. We use the Facebook mobile application, as a test case, to evaluate our proposed framework. Evaluation results have demonstrated the efficacy of the framework in providing network access control measures based on real-time assessment of user's context.

Leveraging Data Intensive Applications on a Pervasive Computing Platform: The Case of MapReduce

Pervasive grids represent an important step towards the establishment of mobiquitous systems, but at the same time these environments are especially challenging when considering data distribution and data intensive processing. In this work we present CloudFIT, a middleware designed to support the volatility of pervasive environments, and discuss the main challenges related to efficiently deploy MapReduce applications on pervasive environments.

Secure health assistance in a ward-based pervasive environment

Healthcare monitoring and its maintenance are on the rise in modern pervasive environment. Pervasive computing is a recent technology which is the integration of virtual and physical environment that is indistinguishable from everyday life. Body sensor network (BSN) supports continuous monitoring of physiological signals of patients in a hospital environment with real-time updates of medical records from the database via internet. Data shared by BSN has to be secured and made confidential. The wireless message transfer in BSN makes it more vulnerable for attacks. In this paper, the essential security provisioning to data sharing using a novel architecture is discussed along with data and key management in ward-based scenario of a hospital environment. The security provisioning is tested with elliptic curve cryptography. This technique is proved superior to the existing techniques in our simulation experiments.

Context-aware Scheduling for Apache Hadoop over Pervasive Environments

This article proposes to improve Apache Hadoop scheduling through the usage of context-awareness. Apache Hadoop is the most popular implementation of the MapReduce paradigm for distributed computing, but its design doesn’t adapt automatically to computing nodes’ context and capabilities. By introducing context-awareness into Hadoop, we intent to dynamically adapt its scheduling to the execution environment. This is a necessary feature in the context of pervasive grids, which are heterogeneous, dynamic and shared environments. The solution has been incorporated into Hadoop and evaluated through controlled experi- ments. The experiments demonstrate that context-awareness provides comparative performance gains, especially when part of the resources disappear during execution.

Smart TV-Smartphone Multiscreen Interactive Middleware for Public Displays.

A new generation of public displays demands high interactive and multiscreen features to enrich people's experience in new pervasive environments. Traditionally, research on public display interaction has involved mobile devices as the main characters during the use of personal area network technologies such as Bluetooth or NFC. However, the emergent Smart TV model arises as an interesting alternative for the implementation of a new generation of public displays. This is due to its intrinsic connection capabilities with surrounding devices like smartphones or tablets. Nonetheless, the different approaches proposed by the most important vendors are still underdeveloped to support multiscreen and interaction capabilities for modern public displays, because most of them are intended for domestic environments. This research proposes multiscreen interactive middleware for public displays, which was developed from the principles of a loosely coupled interaction model, simplicity, stability, concurrency, low latency, and the usage of open standards and technologies. Moreover, a validation prototype is proposed in one of the most interesting public display scenarios: the advertising.

Impact of Signal-Strength on Trusted and Secure Clustering in Mobile Pervasive Environment

This Proposed work is further extension of our previous work, cluster based Soft Security trust metric evaluation in Mobile Pervasive Environment. Pervasive computing has the potential to provide low cost, high performance, and user centric solutions to exchange the information and communicate seamlessly in highly dynamic, heterogeneous environment where small and powerful dissimilar devices or nodes have to establish independent network unknown by the user. Communicating devices or nodes are resource-restricted and equipped with micro or bio sensors to acknowledge the signals. To provide promising level of security assurance traditional security systems based on cryptography and encryption are not sufficient. In this paper we present extension of our previous work where we observe node's impulsive behavior to become malicious as a soft security factors and propose a trusted cluster formation with security and energy efficiency considerations in the subjective area. In this work we analyses impact of signal-strength attacks while cluster communication on trust degree and level of security. In winding up, we put our efforts to validate the proposed approach and present comparison with other similar schemes for significant adaptation of trustworthy and secure communication where information is ubiquitous.

Discreet verification of user identity in pervasive computing environments using a non-intrusive technique

This paper presents a new approach for verifying user identity in pervasive environments using a non-intrusive behaviour tracking technique that offers minimum interruption to the user’s activities. The technique, termed Non-intrusive Identity Assertion System (NIAS), uses knowledge of how the user uses the environment’s services to infer their identity. The technique monitors user behaviour through identifying certain types of activity without the need for detailed tracking of user behaviour, thus minimising intrusion on the user’s normal activities. The technique was evaluated using a simulated environment to assess its reliability. Simulation results show that the technique can be applied in various situations such as strict and relaxed security settings by applying different security policies. They also show that the technique is particularly effective where the environment has a mixture of high and low security resources in which case reliability could exceed 99%.

Optimization of Location Management Cost by Mobility Pattern

As per one survey, every mobile user possesses two mobiles in the ratio of 1:2. Out of this 75% of the mobiles belongs to the category of smart phones. In this situation, the technology also fulfills the requirements for future advanced usage. Now-a-days mobile plays a pivotal role for connecting the global matters with in the hold of our palm. The main factor which influences the availability of mobile system in the market is speed and portability. Hence the speedy retrieval is the tharaga manthra pronounced in the minds of mobile users. In the instant world, time is the major constraint for the user who relies on the performance. If the system contains intelligence the reliability level of the system also increases, otherwise it will go down even to the point of zero.In this paper, we proposed a new mobility management schemes based on mobility pattern to minimize the total cost and to balance the Location update and search Paging. The new system its main aim is to get the speedy retrieval by using mobility pattern. In the new system one mobility pattern is maintained in each and every visited cell. If the number of pattern is increased then the movement weight is reduced and the updation cost and seeking cost is also reduced. Here some cells in the network are designated as reporting cells, mobile terminals update their positions upon entering one of these reporting cells. Due to the popularity and robustness, Genetic algorithm is used to solve the reporting cells planning problem. The new system not only satisfies the requirements of the mobile environment but also fulfills the pervasive environment, because it integrates the concepts of mobile and intelligence. By use of this intelligence, the extraction of output and its level of accuracy are very high. Here intelligence is used to identify the shortest path. The main drawback here is same time taken for first call and maintain less time for subsequent calls only. The performance of the new system can be tested by generating random data sets for number of generations 500 and 1,000, the network size taken is 4X4. Here we have evaluated the performance of the new system by comparing with some existing systems like POFLA, UPBLA and MIPN. The performance can be measured by call-to-mobility ratio, locating time ratio, the update cost ratio, time-data routed ratio. Comparatively the new system is better than any other existing system we have mentioned.

MAPREDUCE CHALLENGES ON PERVASIVE GRIDS

This study presents the advances on designing and implementing scalable techniques to support the development and execution of MapReduce application in pervasive distributed computing infrastructures, in the context of the PER-MARE project. A pervasive framework for MapReduce applications is very useful in practice, especially in those scientific, enterprises and educational centers which have many unused or underused computing resources, which can be fully exploited to solve relevant problems that demand large computing power, such as scientific computing applications, big data processing, etc. In this study, we pro-pose the study of multiple techniques to support volatility and heterogeneity on MapReduce, by applying two complementary approaches: Improving the Apache Hadoop middleware by including context-awareness and fault-tolerance features; and providing an alternative pervasive grid implementation, fully adapted to dynamic environments. The main design and implementation decisions for both alternatives are described and validated through experiments, demonstrating that our approaches provide high reliability when executing on pervasive environments. The analysis of the experiments also leads to several insights on the requirements and constraints from dynamic and volatile systems, reinforcing the importance of context-aware information and advanced fault-tolerance features to provide efficient and reliable MapReduce services on pervasive grids.

Distributed service-based approach for sensor data fusion in IoT environments.

The Internet of Things (IoT) enables the communication among smart objects promoting the pervasive presence around us of a variety of things or objects that are able to interact and cooperate jointly to reach common goals. IoT objects can obtain data from their context, such as the home, office, industry or body. These data can be combined to obtain new and more complex information applying data fusion processes. However, to apply data fusion algorithms in IoT environments, the full system must deal with distributed nodes, decentralized communication and support scalability and nodes dynamicity, among others restrictions. In this paper, a novel method to manage data acquisition and fusion based on a distributed service composition model is presented, improving the data treatment in IoT pervasive environments.