Lanlan Rui¹, Yabin Qin^1,*, Biyao Li¹, Zhipeng Gao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 291-315, 2019, DOI:10.31614/cmes.2018.04240

Abstract Maintenance is an important aspect in the lifecycle of communication network devices. Prevalent problems in the maintenance of communication networks include inconvenient data carrying and sub-optimal scheduling of work orders, which significantly restrict the efficiency of maintenance work. Moreover, most maintenance systems are still based on cloud architectures that slow down data transfer. With a focus on the completion time, quality, and load balancing of maintenance work, we propose in this paper a learning-based virus evolutionary genetic algorithm with multiple quality-of-service (QoS) constraints to implement intelligent scheduling in an edge network. The algorithm maintains the diversity of the population and… More >

Afzal Badshah¹, Anwar Ghani¹, Muhammad Ahsan Qureshi², Shahaboddin Shamshirband,^3,4,*

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 81-101, 2019, DOI:10.32604/cmc.2019.06288

Abstract Educational institutions are soft targets for the terrorist with massive and defenseless people. In the recent past, numbers of such attacks have been executed around the world. Conducting research, in order to provide a secure environment to the educational institutions is a challenging task. This effort is motivated by recent assaults, made at Army Public School Peshawar, following another attack at Charsada University, Khyber Pukhtun Khwa, Pakistan and also the Santa Fe High School Texas, USA massacre. This study uses the basic technologies of edge computing, cloud computing and IoT to design a smart emergency alarm system framework. IoT is… More >

Jaideep Kaur¹, Kamaljit Kaur²

CMC-Computers, Materials & Continua, Vol.53, No.1, pp. 23-36, 2017, DOI:10.3970/cmc.2017.053.024

Abstract The ubiquitous Internet of Things (IoT) through RFIDs, GPS, NFC and other wireless devices is capable of sensing the activities being carried around Industrial environment so as to automate industrial processes. In almost every industry, employee performance appraisal is done manually which may lead to favoritisms. This paper proposes a framework to perform automatic employee performance appraisal based on data sensed from IoT. The framework classifies raw IoT data into three activities (Positive, Negative, Neutral), co-locates employee and activity in order to calculate employee implication and then performs cognitive decision making using fuzzy logic. From the experiments carried out it… More >