General-purpose operating systems, such as Linux, are increasingly being used in embedded systems. Computational resources are usually limited, and embedded processors often have a limited amount of memory. This makes code size especially important. This paper describes techniques for automatically reducing the memory footprint of general-purpose operating systems on embedded platforms. The problem is complicated by the fact that kernel code tends to be quite different from ordinary application code, including the presence of a significant amount of hand-written assembly code, multiple entry points, implicit control flow paths involving interrupt handlers, and frequent indirect control flow via function pointers. We use a novel "approximate decompilation" technique to apply source-level program analysis to hand-written assembly code. A prototype implementation of our ideas on an Intel x86 platform, applied to a Linux kernel that has been configured to exclude unnecessary code, obtains a code size reduction of close to 24%

There is increasing interest in using general-purpose operating systems, such as Linux, on embedded platforms. It is especially important in embedded systems to use memory efficiently because embedded processors often have limited physical memory. This paper describes an automatic technique for reducing the memory footprint of general-purpose operating systems on embedded platforms by keeping infrequently executed code on secondary storage and loading such code only if it is needed at run time. Our technique is based on an old idea - memory overlays - and it does not require hardware or operating system support for virtual memory. A prototype of the technique has been implemented for the Linux kernel. We evaluate our approach with two benchmark suites: MiBench and MediaBench, and a Web server application. The experimental results show that our approach reduces memory requirements for the Linux kernel code by about 53% with little degradation in performance.

Traditional content distributions such as Web cache and content distribution networks need to reconfigure the networks or purchase additional servers to support these services. While P2P content distribution networks do not change the underlying infrastructure. We propose to build the multi-P2P networks based on the current unstructured and structured P2P networks. And the contents are distributed between multi-P2P networks. We explore the stochastic fluid analytical models for the purpose of multi-P2P networks performance. And we get the results of the relation between the content get probability and the number of multi-P2P networks, number of nodes, users' request rate, content expiration rate through this analytical model. The number of multi-P2P networks has a more impact on the content get probability than that of the universal P2P network. It has been proved that the scheme of constructing multi-P2P networks is effective.

Software debugging is the process of locating and correcting faulty code. Prior techniques to locate faulty code either use program analysis techniques such as backward dynamic program slicing or exclusively use delta debugging to analyze the state changes during program execution. In this paper, we present a new approach that integrates the potential of delta debugging algorithm with the benefit of forward and backward dynamic program slicing to narrow down the search for faulty code. Our approach is to use delta debugging algorithm to identify a minimal failure-inducing input, use this input to compute a forward dynamic slice and then intersect the statements in this forward dynamic slice with the statements in the backward dynamic slice of the erroneous output to compute a failure-inducing chop. We implemented our technique and conducted experiments with faulty versions of several programs from the Siemens suite to evaluate our technique. Our experiments show that failure-inducing chops can greatly reduce the size of search space compared to the dynamic slices without significantly compromising the capability to locate the faulty code. We also applied our technique to several programs with known memory related bugs such as buffer overflow bugs. The failure-inducing chop in several of these cases contained only 2 to 4 statements which included the code causing memory corruption.