Shameem Ahmed

MARKS (Middleware Adaptability for Resource Discovery, Knowledge Usability and Self-healing) for Mobile Devices of Pervasive Computing Environments

With the tremendous increase in the use of mobile handheld and wearable devices, the pervasive computing arena is becoming stronger and powerful day by day. Despite having various physical constraints, many of the resource-rich functionalities enjoyed by other devices have been incorporated in these tiny devices. This is why different fields of research have developed in this area. There are still some unexplored but crucial features like knowledge usability, resource discovery, and self-healing that deserve further attention. Besides exploration of these areas, implementation and evaluation of these features need to be considered from a security and privacy perspective. In this paper, we illustrate the design and implementation of a middleware MARKS, which incorporates these less-explored areas of pervasive computing, to guarantee optimum utilization of the physical capabilities and also to ensure security and privacy

An adaptive lightweight trust reliant secure resource discovery for pervasive computing environments

A secure resource discovery model for devices running in pervasive computing environments has become significant. Due to the constrained nature of these devices, the need for a model that allows discovery and sharing of resources without putting much overhead on the operation of devices is needed. The dependency on fixed powerful machines for ensuring security is not desired and also not feasible. In this paper, we present a resource discovery model that provides security whenever needed without degrading the performance of the device. We also propose a trust based service-oriented adaptive security mechanism named SSRD (simple and secure resource discovery)

ETS (Efficient, Transparent, and Secured) Self-healing Service for Pervasive Computing Applications

To ensure smooth functioning of numerous handheld devices anywhere anytime, the importance of self-healing mechanism cannot be overlooked. Incorporation of efficient fault detection and recovery in device itself is the quest for long but there is no existing self-healing scheme for devices running in pervasive computing environments that can be claimed as the ultimate solution. Moreover, the highest degree of transparency, security and privacy attainability should also be maintained. ETS Self-healing service, an integral part of our developing middleware named MARKS (Middleware Adaptability for Resource discovery, Knowledge usability, and Self-healing), holds promise for offering all of those functionalities.

Self-healing for autonomic pervasive computing

Self-healing is one of the main challenges to growing autonomic pervasive computing. Fault detection and recovery are the main steps of self-healing. Due to the characteristics of pervasive computing the self-healing becomes difficult. In this paper, the challenges of self-healing have been addressed and an approach to develop a self-healing service for autonomic pervasive computing is presented. The self-healing service has been developed and integrated into the middleware named MARKS+ (Middleware Adaptability for Resource discovery, Knowledge usability, and Self-healing). The self-healing approach is being evaluated on a test bed of PDAs. An application is being developed by using the proposed service.

SSRD+: A Privacy-aware Trust and Security Model for Resource Discovery in Pervasive Computing Environment

SSRD is a secure resource discovery model for devices running in a pervasive computing environment. SSRD is based on a lightweight trust model. SSRD+ is an extension of the existing SSRD model. In SSRD+, we enhance the trust model by adding dynamic trust relationship and also specifying behavioral characteristics that determine the level of trust among devices. We also add a risk model to address challenges posed by the pervasive and ad hoc nature of the network. These models work together to make the entire discovery process lightweight and secure. In this paper we present details of the trust and risk models. We illustrate the design and implementation of SSRD+ as a whole that optimally explores resources without degrading the performance of the devices while ensuring user security and privacy

A Risk-aware Trust Based Secure Resource Discovery (RTSRD) Model for Pervasive Computing

To address the challenges posed by device capacity and capability, and also the nature of ad-hoc network of pervasive computing, a resource discovery model is needed that can resolve security and privacy issues with simple solutions. The use of complex algorithms and powerful fixed infrastructure is infeasible due to the volatile nature of pervasive environment and tiny pervasive devices. In this paper, we present a risk- aware trust based secure resource discovery model, RTSRD (risk-aware trust based secure resource discovery) for a truly pervasive environment. Our model is an adaptive hybrid one that allows both secure and non-secure discovery of services on adaptive trust. RTSRD also incorporates a risk model for sharing resources with unknown devices. Hence, the two contributions of this paper are: adaptive trust, and risk model for resource discovery in pervasive computing environments.

A smart meeting room with pervasive computing technologies

Usability of pervasive computing features along with the detection of a meeting is very effective for the users. In this paper, we present the design of a smart meeting room (SMR) that not only detect the starting and ending of a meeting but also provide the support of participants context information, knowledge usability and ephemeral group communication. Our approach will play a vital role for not only for meeting detection but other closely related applications of pervasive computing.

Zero-knowledge real-time indoor tracking via outdoor wireless directional antennas

WiFi localization and tracking of indoor moving objects is an important problem in many contexts of ubiquitous buildings, first responder environments, and others. Previous approaches in WiFi-based indoor localization and tracking either assume prior knowledge of indoor environment or assume many data samples from location-fixed WiFi sources (i.e. anchor points). However, such assumptions are not always true, especially in emergency scenarios. This paper explores the possibility of real-time indoor localization and tracking without any knowledge of indoor environment and with real-time data samples from only few anchor points outside the building. By using a small set of synchronized directional antennas as outdoor anchor points to actively scan in various directions, a moving device inside the building can be localized and tracked from the received signal in real-time manner. The paper proposes an angle-of-arrival estimator for accurate localization and adaptive per-antenna angular scheduling for real-time indoor tracking. The validation results from real experiment and simulation yield effectiveness and accuracy of the proposed schemes.

PerAd-Service: a middleware service for pervasive advertisement in m-business

In this paper, primarily, we delineate the numerous challenges that can arise in mobile-business (m-business) to provide the highest degree of proliferation of pervasive advertisement. Later, we demonstrate the feasibility of PerAd-Service, an integral part of, MARKS (middleware adaptability for knowledge usability, resource discovery, and self-healing) to address those challenges.

Topology-aware Optimal Task Allocation for publish/subscribe-based mission critical environment

A mission critical environment (MCE) consists of error-prone, highly variable, and highly rate limited communication channels. Paradoxically, this substantially increases the need to perform optimal task allocation (OTA), while at the same time making it much harder to perform OTA efficiently. To simplify the problem, we consider OTA for publish/subscribe-based MCE since it has unique characteristics such as high level publish/subscribe node and task differentiation and high scalability. In this work, we formulate the OTA problem for publish/subscribe-based MCEs, propose an architectural framework and distributed communication protocols emphasizing the unique challenges of MCE. We adopt well-known Hungarian method and Rectangular Assignment algorithm to solve OTA problem in publish/subscribe-based MCE in polynomial time. Through simulations, we evaluate the performance of our proposed system for multiple publish/subscribe scenarios. Our results indicate that our proposed solutions achieve the goal of OTA in highly dynamic environments, with low processing time and communication overhead.