Crowd sensing exploits users' smart devices and human mobility to collect information on a large scale. To realize a crowd sensing campaign, sensing tasks with spatio-temporal requirements are distributed to the devices that can provide the requested information. Typically, the distribution of sensing tasks relies on a centralized communication infrastructure such as cloud servers. However, such an approach will be unsuitable if access to communication infrastructure is restricted, for example in disaster relief scenarios. To fill this gap, we propose a distributed context-aware framework for disseminating sensing tasks, based on the Named Data Networking (NDN) paradigm. By adding context attributes to Interest packets, we allow a device to utilize this information to make forwarding decisions autonomously, thus guiding the sensing tasks towards the suitable sensing devices. Through intensive evaluation, we show that our framework achieves a timely delivery of sensing tasks, while keeping the communication overhead to a minimum compared to pure geo forwarding and flooding approaches.

The advent of the Internet of Things (IoT), with modern sensors and sensor-based devices, will significantly stimulate the development of context-aware applications. An effective means to extract higher-level contextual information from sensor data is distributed complex event processing (CEP), which facilitates the analysis of real-time data streams coming from heterogeneous and distributed sources. Considering that user context is inherently sensitive information, the preservation of privacy is critical once the processing of user context takes place over several (possibly malicious) devices, especially in collaborative scenarios. In this paper, we tackle this issue by introducing a trust-based approach for the placement and execution of CEP operators in a distributed environment. We propose a trust management model based on communication interactions among the users. Furthermore, we incorporate trust recommendations using a cosine-based similarity check in order to overcome collusion and on-off attacks. We developed a smartphone-based distributed CEP system called TrustCEP to evaluate our approach for trust management. Based on the evaluation of TrustCEP, we observe that our approach induces a minimal increase in average battery consumption compared to privacy-negligent approaches.

In recent times, the working society has been plagued by a work-life imbalance as a result of the added flexibility introduced by advanced information and communication technology. A technically viable approach to improve one's work-life balance is to control the communication mediums depending on the respective user contexts, and consequently help the users maintain their concentration. To achieve this, an important prerequisite is the efficient exchange of context information among the users. Therefore, this paper motivates a novel decentralized approach which facilitates context data exchange as per prevailing conditions on privacy and confidentiality. We discuss the governing criteria surrounding user contexts and draw the main design challenges with respect to the proposed system, accordingly.