The distributed computing systems place greater demands on incremental state recognition， node consistency synchronization， and seamless service switching during continuous task running. However， the existing mechanisms still have limitations in awareness of cluster state structure， node consistency control， and controllable service version switching， which hinder stable service running under frequent state evolution. Therefore， Zynco was proposed， a lightweight and distributed framework for runtime state coevolution. Zynco was designed with three core mechanisms： a fingerprint-based and structure-aware incremental recognition mechanism， by which only effective state changes were transmitted and a sliding version chain was maintained； a feedback protocol combining User Datagram Protocol （UDP） multicast with Transmission Control Protocol （TCP） control channels， to achieve efficient distribution and acknowledgment of state among multiple nodes； a three-layer service structure with listener-based routing， thereby enabling smooth service switching and consistent rollback. Experimental results show that， in a 20-node cluster， Zynco requires only 27 s to complete state synchronization for incremental updates involving 54 GB of file data， without task interruption or state tearing during service switching； under a 1 000 QPS （Queries Per Second） load， Zynco has the response jitter time below 8 ms. It can be seen that Zynco is efficient， stable， controllable， and can provide good operational support for state?driven distributed high?performance services in massive?data collaborative update scenarios.

Private data is easy to suffer from the attacks about data confidentiality, integrity and freshness. To resolve this problem, a secure data aggregation algorithm based on homomorphic Hash function was proposed, called HPDA (High-Efficiency Privacy Preserving Data Aggregation) algorithm. Firstly, it used homomorphic encryption scheme to provide data privacy-preserving. Secondly, it adopted homomorphic Hash function to verify the integrity and freshness of aggregated data. Finally, it reduced the communication overhead of the system by improved ID transmission mechanism. The theoretical analyses and experimental simulation results show that HPDA can effectively preserve data confidentiality, check data integrity, satisfy data freshness, and bring low communication overhead.

With the intensive research and application of cloud computing, the problems about the security and privacy protection of the data stored on the remote server become hot issues of business and academia. Traditional cryptography methods can partly solve the above problems, but bring lots of obstacles to the remote user for data query and usage as well. Searchable encryption is an option to solve this contradiction, because of which enables users to search encrypted data stored on remote server, and has become a research hotspot in the field of information security at present. An overview of the public key searchable encryption was made in this paper, of which especially focused on the origin, background and research results in recent years of the Public key Encryption with Keyword Search (PEKS). The PEKS formal definition and security model definitions were given, followed by the detail discussion about the other aspects of this domain, such as the PEKS secure channel dependency problem, the query functional improvement, et al. Finally, the future trends, hotspot and open-ended problems of this novel research area were put forward.

To solve the difficulty and complexity of symbol timing problem of Multi-h CPM (Continuous Phase Modulation), a non-data-aided feedforward symbol timing recovery algorithm for multi-h CPM was proposed. The joint likelihood functions of modulation index offset and symbol timing offset were simplified into the likelihood functions of symbol timing offset and estimation of symbol timing offset was acquired by means of averaging the expectation functions according to possible modulation index offset. Modified Cramer-Rao Bound (MCRB) and implementation scheme of the proposed symbol timing recovery were presented. The simulation analyses show that, the proposed algorithm is suitable for full response and partial response multi-h CPM. Meanwhile, symbol timing recovery performance is good, and is not sensitive to the carrier frequency offset and modulation index offset.

Concerning the problems of large amount of calculation and poor accuracy of traditional matching method of plane image target point, a fast and highly precise matching method of plane image target point was proposed based on RANdom SAmple Consensus (RANSAC) random sampling algorithm. Firstly, based on the dual conic model, the ellipse's gradient vector was estimated by exploiting directly the raw gradient information in the neighborhood of an ellipse's boundary. Secondly, the ellipse's parameters and centers with the gradient vector field were matched. At last, the points in image with the target point in calibration board were matched with the help of RANSAC random sampling algorithm. The experimental results verify the method is simple and has a high degree of accuracy.

VCR operations are important functions of streaming media servers. Most of conventional caching algorithms implemented by media servers do not consider the impact of VCR operations. Based on the SRB algorithm and combining patching technology, a kind of shared cache algorithm named SRC-SV was proposed, which supported VCR operations. The simulation results show that the SRC-SV algorithm can be used to handle VCR operations and be effective in reducing consumption of server's load and backbone bandwidth.