| 1. |
- Sari, Alparslan, et al.
(författare)
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A case study of decision support system and warehouse management system integration
- 2021
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Ingår i: Decision Support Systems and Industrial IoT in Smart Grid, Factories, and Cities. - : IGI Global. ; , s. 111-138
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- A warehouse is an indispensable part of the logistics. A warehouse management system (WMS) is designed to improve efficiency in warehouses to increase their throughput and potential. The rise of IoT and its commercialization enabled 'smart things' to be widely adopted by hobbyists and companies. Cheap sensors and smart devices triggered better automation opportunities. Many devices and sensors that are being deployed in the industry and warehousing are affected by this trend. A well-designed WMS is needed to connect devices and humans in a heterogenous warehouse environment. This chapter introduces a prototype of a WMS powered by a decision support system (DSS) based on real-life requirements. In order to have fast, reliable, and efficient decision making in warehousing, the importance of employing DSS in the WMS is emphasized. Warehouse-related IoT technology is briefly introduced, and its security considerations are discussed thoroughly. The main contribution of this chapter is to show how warehouse operations can be modeled in business process model notation and executed in a DSS.
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| 2. |
- Sari, Alparslan, et al.
(författare)
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A Highly Scalable Instruction Scheduler Design based on CPU Stall Elimination
- 2021
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Ingår i: 2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021. ; , s. 105-110
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Konferensbidrag (refereegranskat)abstract
- In this paper, by targeting low-level code optimization, an instruction scheduler is designed and experimented with a synergistic processor unit (SPU) to show its effectiveness on a basic block and data dependency graph (DDG) called compiler instruction scheduler (CIS). In our methodology, a source C/C++ file is converted to an assembly file via spu-gcc to detect stalls in basic code blocks and CIS generates the DDG of executable code to eliminate stalls to find optimization opportunities and increase the program performance. The CIS simply shuffles the instruction sequences of the assembly code to eliminate CPU stalls in a given basic instruction block. Random and sliding window schedulers are implemented to generate a new assembly code sequence based on DDG and a basic block in parallel. Finally, this paper describes how CIS finds the optimized code sequence for a given file without any conflicts and hazards. Compared to the original code compilation process, we have shown that CIS improves the code execution metrics, and also our evaluated speedup results are found to be promising.
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| 3. |
- Sari, Alparslan, et al.
(författare)
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Designing a Distributed Multi-agent System for Compiler Optimization
- 2021
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Ingår i: 2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021. ; , s. 269-274
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Konferensbidrag (refereegranskat)abstract
- This paper explores the run time performance improvements using different GCC optimization flags in program compilation. As multi-core microprocessor systems replacing legacy single-core ones, tremendous effort is needed to address to optimize the associated compilers for newly designed architectures in order to suit them for running parallel programming on multiple cores. Therefore, the aim of this paper is to address this challenge by designing an optimum distributed multi-agent system to perform compiler optimization. A multi-agent framework is adopted to utilize random and genetic algorithm-based search algorithm to find the best GCC optimization flags for a given program. The framework is highly scalable and can be extended with distributed system concept to perform code compilation in parallel to find the best-optimized code sequence in a short amount of time. The initial performance results have promising indicators which clearly show that the performance improvement is achieved.
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| 4. |
- Sari, Alparslan, et al.
(författare)
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Early Detection and Recovery Measures for Smart Grid Cyber-Resilience
- 2021
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Ingår i: Decision Support Systems and Industrial IoT in Smart Grid, Factories, and Cities. - Hershey, PA, USA : IGI Global. ; , s. 91-110
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- The internet of things (IoT) has recently brought major technological advances in many domains, including the smart grid. Despite the simplicity and efficiency that IoT brings, there are also underlying risks that are slowing down its adoption. These risks are caused by the presence of legacy systems inside existing infrastructures that were built with no security in mind. In this chapter, the authors propose a method for early-stage detection of cyber-security incidents and protection against them through applicable security measures. This chapter introduces security techniques such as anomaly detection, threat investigation through a highly automated decision support system (DSS), as well as incident response and recovery for smart grid systems. The introduced framework can be applied to industrial environments such as cyber-threats targeting the production generator as well as the electricity smart meters, etc. The chapter also illustrates the framework's cyber-resilience against zero-day threats and its ability to distinguish between operational failures as well as cyber-security incidents.
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