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Mobile, pervasive computing environments respond to users' requirements by providing access to and composition of various services over networked devices. In such an environment, service composition needs to satisfy a request's goal, and be mobile-aware even throughout service discovery and service execution. A composite service also needs to be adaptable to cope with the environment's dynamic network topology. Existing composition solutions employ goal-oriented planning to provide flexible composition, and assign service providers at runtime, to avoid composition failure. However, these solutions have limited support for complex service flows and composite service adaptation. This paper proposes a self-organizing, goal-driven service model for task resolution and execution in mobile pervasive environments. In particular, it proposes a decentralized heuristic planning algorithm based on backward-chaining to support flexible service discovery. Further, we introduce an adaptation architecture that allows execution paths to dynamically adapt, which reduces failures, and lessens re-execution effort for failure recovery. Simulation results show the suitability of the proposed mechanism in pervasive computing environments where providers are mobile, and it is uncertain what services are available. Our evaluation additionally reveals the model's limits with regard to network dynamism and resource constraints.

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Through offloading the computing tasks of the task nodes (TNs) to the fog nodes (FNs) located at the network edge, the fog network is expected to address the unacceptable processing delay and heavy link burden existed in current cloudbased networks. Unlike most existing researches based on the command-mode offloading and full capability report, this paper develops a general analytical model of the task scheduling among voluntary nodes (VNs) in fog networks, wherein the VNs voluntarily contribute their capabilities for serving their neighboring TNs. A novel Delay-Optimal Task Scheduling (DOTS) algorithm is proposed to obtain the delay-optimal offloading solution according to the reported capabilities of the VNs. Extensive simulations are carried out in a fog network, and the numerical results indicate that the proposed DOTS algorithm can effectively provide the optimal helper nodes (HNs) set, subtask sizes, and TN transmission power to minimize the overall task processing delay. Moreover, compared with the command-mode offloading, the voluntary-mode achieves more balanced offloading and a higher fairness level among the FNs.

Ciphertext-policy attribute-based encryption (CP-ABE) provides an encrypted access control mechanism for broadcasting messages. Basically, a sender encrypts a message with an access control policy tree which is logically composed of attributes; receivers are able to decrypt the message when their attributes satisfy the policy tree. A user's attributes stand for the properties that he currently owns. A user should keep his attributes up-to-date. However, this is not easy in CP-ABE because whenever one attribute changes, the entire private key, which is based on all the attributes, must be changed. In this paper, we introduce fading function, which renders attributes "dynamic" and allows users to update each attribute separately. We study how choosing fading rate for fading function affects the efficiency and security. We also compare our design with CP-ABE and find our scheme performs significantly better under certain circumstance.

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