Biblio

Due to their low complexity and robustness in nature, wireless sensor networks are a key component in cyber-physical system. The integration of wireless sensor network in cyber-physical system provides immense benefits in distributed controlled environment. However, the open nature of the wireless medium makes resource-constrained WSN vulnerable to unauthorized interception and detection. Privacy is becoming one of the major issues that jeopardize the successful deployment of WSN. In this paper, we propose a scheme named HASHA to provide location privacy. Different from previous approaches, HASHA protect nodes' location privacy at data link layer. It is well known that payload at data link layer frame is well protected through cryptosystem, but addresses at data link layer leaves unprotected. The adversaries can identify nodes in the network easily by capturing frames and check the source and destination addresses. If both addresses are well protected and unknown to the adversaries, they cannot identify nodes of the targeted networks, rendering it very difficult to launch traffic analysis and locate subjects. Simulation and analytical results demonstrate that our scheme provides stronger privacy protection and requires much less energy.

Optimizing memory access is critical for performance and power efficiency. CPU manufacturers have developed sampling-based performance measurement units (PMUs) that report precise costs of memory accesses at specific addresses. However, this data is too low-level to be meaningfully interpreted and contains an excessive amount of irrelevant or uninteresting information. We have developed a method to gather fine-grained memory access performance data for specific data objects and regions of code with low overhead and attribute semantic information to the sampled memory accesses. This information provides the context necessary to more effectively interpret the data. We have developed a tool that performs this sampling and attribution and used the tool to discover and diagnose performance problems in real-world applications. Our techniques provide useful insight into the memory behaviour of applications and allow programmers to understand the performance ramifications of key design decisions: domain decomposition, multi-threading, and data motion within distributed memory systems.