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Construction of a Retargetable Compiler Generation System from Machine Behavioral Description (머쉰 행위기술로부터 Retargetable 컴파일러 생성시스템 구축)

  • Lee, Sung-Rae;Hwang, Sun-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.5B
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    • pp.286-294
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    • 2007
  • In ASIP design, compiler is required for performance evaluation of processors being designed. The design of machine specific compiler is time consuming. This paper presents the system which generates C compiler from MDL descriptions. Compiler generation using MDL can support user retargetability and concurrency between compiler design and processor design. However, it must overcome semantics gap between compiler and machine. To handle this problem, the proposed system maps behavioral descriptions to library which contains abstract behavior for each tree pattern. Using mapped instructions and information on register file usage, the proposed system generates back-end interface function of the compiler. Generated compilers, for MIPS R3000, ARM9 cores, have been proved by application programs written in C code.

Security Analysis of Information Flow using SAT (SAT를 이용한 정보흐름의 안전성 분석)

  • Kim, Je-Min;Kouh, Hoon-Joon
    • Journal of Digital Convergence
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    • v.14 no.6
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    • pp.253-261
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    • 2016
  • As many people use internet through the various programs of PC and mobile devices, the possibility of private data leak is increasing. A program should be used after checking security of information flow. Security analysis of information flow is a method that analyzes security of information flow in program. If the information flow is secure, there is no leakage of personal information. If the information flow not secure, there may be a leakage of personal information. This paper proposes a method of analyzing information flow that facilitates SAT solver. The method translates a program that includes variables where security level is set into propositional formula representing control and information flow. The satisfiability of the formula translated is determined by using SAT solver. The security of program is represented through the result. Counter-example is generated if the program is not secure.

A Bio-inspired Hybrid Cross-Layer Routing Protocol for Energy Preservation in WSN-Assisted IoT

  • Tandon, Aditya;Kumar, Pramod;Rishiwal, Vinay;Yadav, Mano;Yadav, Preeti
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.4
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    • pp.1317-1341
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    • 2021
  • Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.