Current Issue : July - September Volume : 2018 Issue Number : 3 Articles : 5 Articles
Even if a collision occurs in IEEE 802.11 network, a transmissionmay be successfully decoded at the receiver if the signal strength of\none transmission is sufficiently stronger than the other transmission. This phenomenon is called ââ?¬Å?Physical Layer Captureââ?¬Â (PLC).\nWhile existing works have considered PLC between data frames, in this paper we investigate the case that an ACK frame collides\nwith the unfinished transmission of other data frames after the occurrence of PLC between data frames. As a result of this collision,\nthe ACK frame may be corrupted and the corresponding data frame needs to be retransmitted. We call this phenomenon ââ?¬Å?ACK\nCorruptionââ?¬Â (AC).We identify the characteristic of AC via extensive experiments and simulations. Our study reveals that AC can\noccur in all IEEE 802.11 variants and its chance is dependent upon the relative signal strength between the stations and the MCS\nsetting used. Further, we devise a way to avoid AC occurrence and evaluate its effectiveness....
Software Defined Network separates the control plane from network equipment and has great advantage in network management\nas compared with traditional approaches. With this paradigm, the security issues persist to exist and could become even worse\nbecause of the flexibility on handling the packets. In this paper we propose an effective framework by integrating SDN and machine\nlearning to detect and categorize P2P network traffics. This work provides experimental evidence showing that our approach can\nautomatically analyze network traffic and flexibly change flow entries in OpenFlow switches through the SDN controller. This can\neffectively help the network administrators manage related security problems....
Effective data access is one of the major challenges in Delay Tolerant Networks (DTNs) that are characterized by intermittent\nnetwork connectivity and unpredictable node mobility. Currently, different data caching schemes have been proposed to improve\nthe performance of data access in DTNs. However, most existing data caching schemes perform poorly due to the lack of global\nnetwork state information and the changing network topology in DTNs. In this paper, we propose a novel data caching scheme\nbased on cooperative caching in DTNs, aiming at improving the successful rate of data access and reducing the data access delay. In\nthe proposed scheme, learning automata are utilized to select a set of caching nodes as CachingNode Set (CNS) inDTNs.Unlike the\nexisting caching schemes failing to address the challenging characteristics of DTNs, our scheme is designed to automatically selfadjust\nto the changing network topology through the well-designed voting and updating processes. The proposed scheme improves\nthe overall performance of data access in DTNs compared with the former caching schemes. The simulations verify the feasibility\nof our scheme and the improvements in performance...
The scale and complexity of software systems are constantly increasing, imposing new challenges for software fault location and\ndaily maintenance. In this paper, the Security Feature measurement algorithm of Frequent dynamic execution Paths in Software,\nSFFPS, is proposed to provide a basis for improving the security and reliability of software. First, the dynamic execution of a\ncomplex software system is mapped onto a complex network model and sequence model.This, combined with the invocation and\ndependency relationships between function nodes, fault cumulative effect, and spread effect, can be analyzed. The function node\nsecurity features of the software complex network are defined and measured according to the degree distribution and global step\nattenuation factor. Finally, frequent software execution paths are mined and weighted, and security metrics of the frequent paths\nare obtained and sorted. The experimental results show that SFFPS has good time performance and scalability, and the security\nfeatures of the important paths in the software can be effectively measured. This study provides a guide for the research of defect\npropagation, software reliability, and software integration testing...
Seismic reflection is one of the most popular methods in geophysical prospecting. Nevertheless, obtaining high resolution and\naccurate results requires a sophisticated processing stage. There are many open-source seismic reflection data processing software\nprograms available; however, they often use a high-level programming language that decreases its overall performance, lacks\nintuitive user-interfaces, and is limited to a small set of tasks. These shortcomings reveal the need to develop new software\nusing a programming language that is natively supported by Windows operating systems, which uses a relatively medium-level\nprogramming language (such as C#) and can be enhanced by an intuitive user interface. SEISGAMA was designed to address this\nneed and employs a modular concept, where each processing group is combined into one module to ensure continuous and easy\ndevelopment and documentation. SEISGAMA can perform basic seismic reflection processes. This ability is very useful, especially\nfor educational purposes or during a quality control process (in the acquisition stage). Those processes can be easily carried out by\nusers via specific menus on SEISGAMA�s main user interface. SEISGAMA has been tested, and its results have been verified using\navailable theoretical frameworks and by comparison to similar commercial software...
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