Browsing by Author "Aloqaily, Moayad"
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Item Artificial intelligence implication on energy sustainability in Internet of Things: A survey(Elsevier Ltd, 2023-03) Charef, Nadia; Ben Mnaouer, Adel; Aloqaily, Moayad; Bouachir, Ouns; Guizani, MohsenItem Batch-based power-controlled channel assignment for improved throughput in software-defined networks(Institute of Electrical and Electronics Engineers Inc., 2019) Salameh, Haythem Bany; Musa, Ahmed; Outoom, Ruba; Halloush, Rami; Aloqaily, Moayad; Jararweh, YaserSoftware-defined networking (SDN) along with transmission power control (TPC) have a great potential in enabling efficient wireless networking. Power control aims at increasing network throughput, while SDN provides cognition and intelligent capabilities to network devices. The key challenge in enabling efficient operation of such networks is how to perform efficient power-controlled MAC protocols that includes channel assignment and power allocation such that network throughput is enhanced while using the least number of channels. Traditional MAC protocols for SDNs employ an exclusive channel-occupancy between neighboring secondary users (SUs), which significantly limits network performance. In this paper, we develop a novel power-controlled spectrum access protocol for SDNs based on the interference-channel occupancy model with the objective of increasing network throughput. It allows several concurrent interference-limited transmissions to simultaneously proceed over the same channel in the same neighborhood. Unlike most of previous power-control MAC protocols that perform the channel assignment and power allocation sequentially, our protocol simultaneously makes distributed channel and power assignment decisions for multiple SU transmissions (batch-based method). Batching can be achieved by using an admission control window for SUs to exchange their collision-avoidance control information. Simulation results reveal that compared with CSMA/CA variants, our protocol greatly improve spectrum efficiency, which improves network throughput while reducing energy consumption. © 2019 IEEE.Item Cluster aware mobility encounter dataset enlargement(Institute of Electrical and Electronics Engineers Inc., 2019) Haldar, Rajarshi; Bacanli, Salih Safa; Aloqaily, Moayad; Mnaouer, Adel Ben; Turgut, DamlaThe recent emerging fields in data processing and manipulation has facilitated the need for synthetic data generation. This is also valid for mobility encounter dataset generation. Synthetic data generation might be useful to run research-based simulations and also create mobility encounter models. Our approach in this paper is to generate a larger dataset by using a given dataset which includes the clusters of people. Based on the cluster information, we created a framework. Using this framework, we can generate a similar dataset that is statistically similar to the input dataset. We have compared the statistical results of our approach with the real dataset and an encounter mobility model generation technique in the literature. The results showed that the created datasets have similar statistical structure with the given dataset. © 2019 IEEE.Item Data and service management in densely crowded environments : challenges, opportunities, and recent developments(Institute of Electrical and Electronics Engineers Inc., 2019) Aloqaily, Moayad; Ridhawi, Ismaeel Al; Salameh, Haythem Bany; Jararweh, YaserDensely crowded environments such as stadiums and metro stations have shown shortcomings when users request data and services simultaneously. This is due to the excessive amount of requested and generated traffic from the user side. Based on the wide availability of user smart-mobile devices, and noting their technological advancements, devices are not being categorized only as data/service requesters anymore, but are readily being transformed to data/service providing network-side tools. In essence, to offload some of the workload burden from the cloud, data can be either fully or partially replicated to edge and mobile devices for faster and more efficient data access in such dense environments. Moreover, densely crowded environments provide an opportunity to deliver, in a timely manner, through node collaboration, enriched user-specific services using the replicated data and device-specific capabilities. In this article, we first highlight the challenges that arise in densely crowded environments in terms of data/service management and delivery. Then we show how data replication and service composition are considered promising solutions for data and service management in densely crowded environments. Specifically, we describe how to replicate data from the cloud to the edge, and then to mobile devices to provide faster data access for users. We also discuss how services can be composed in crowded environments using service-specific overlays. We conclude the article with most of the open research areas that remain to be investigated. © 2019 IEEE.Item Hierarchical timed colored petri-net based modeling and evaluation of a bank credit monitoring system(IEEE Computer Society, 2019-11) Mnaouer, Adel Ben; Wanis, Marina M.; Aloqaily, MoayadNon-performing assets (NPAs) or bad loans limit the banks from lending to new borrowers. As a result, this would slow down the credit utilization that ends up lowering the deposit interest rates and raising the lending rates, thus, discouraging authentic borrowers. This paper presents a Hierarchical Timed Colored Petri Net (HTCPN) based model that simulates an intelligent agents system which automates credit monitoring and follow-ups by relationship managers (RMs) in bank branches. Efficient follow-ups help the RMs track the borrower's repayment and assess the current values of their counter-assets regularly. In case any loan is kept unattended by the responsible RM, an automated reporting escalation is initiated according to an escalation matrix when due checking time is reached. The HTCPN helped model the expected behaviour of the intelligent agents system used for loan monitoring and also allowed to model a scoring system that is used to monitor the performance of the RMs in handling the loans under their authority and the punctuality of their actions. The performance evaluation through cpn tools simulation resulted in performance ranking and scoring of the RMs, and helped collect statistics on the overall performance of the bank that pointed out to the stages and locations where the flaws are more severe thus providing decision support utilities. © 2019 IEEE.Item An intrusion detection system for connected vehicles in smart cities(Elsevier B.V., 2019-07) Aloqaily, Moayad; Otoum, Safa; Ridhawi, Ismaeel Al; Jararweh, YaserItem A mobility management architecture for seamless delivery of 5G-IoT services(Institute of Electrical and Electronics Engineers Inc., 2019) Balasubramanian, Venkatraman; Zaman, Faisal; Aloqaily, Moayad; Ridhawi, Ismaeel Al; Jararweh, Yaser; Salameh, Haythem BanyMobile Edge Computing (MEC) and Network Slicing techniques have a potential to augment 5G-IoT network services. Telecommunication operators use a diverse set of radio access technologies to provide services for users. Mobility management is one such service that needs attention for new 5G deployments. The QoS requirements in 5G networks are user specific. Network slicing along with MEC has been promoted as a key enabler for such on-demand service schemes. This paper focuses on radio resource access across heterogeneous networks for mobile roaming users. A unified service architecture is proposed enabling seamless handover between a 5G (New Generation Core) service and a 4G (Evolved Packet Core) service via the network slicing paradigm. An identifier-locator (I-L) concept that allows active source-IP sessions is used to handle the seamless hand-over. Signaling costs, service disruptions and other resource reservation requirements are considered in the evaluation to assure that profit for mobile edge operators is achieved. Simulation experiments are considered to provide performance comparisons against the state-of-the-art Distributed Mobility Management Protocol (DMM). © 2019 IEEE.Item Reinforcing the Edge: Autonomous Energy Management for Mobile Device Clouds(Institute of Electrical and Electronics Engineers Inc., 2019) Balasubramanian, Venkatraman; Zaman, Faisal; Aloqaily, Moayad; Alrabaee, Saed; Gorlatova, Maria; Reisslein, MartinThe collaboration among mobile devices to form an edge cloud for sharing computation and data can drastically reduce the tasks that need to be transmitted to the cloud. Moreover, reinforcement learning (RL) research has recently begun to intersect with edge computing to reduce the amount of data (and tasks) that needs to be transmitted over the network. For battery-powered Internet of Things (IoT) devices, the energy consumption in collaborating edge devices emerges as an important problem. To address this problem, we propose an RL-based Droplet framework for autonomous energy management. Droplet learns the power-related statistics of the devices and forms a reliable group of resources for providing a computation environment on-the-fly. We compare the energy reductions achieved by two different state-of-the-art RL algorithms. Further, we model a reward strategy for edge devices that participate in the mobile device cloud service. The proposed strategy effectively achieves a 10% gain in the rewards earned compared to state-of-the-art strategies. © 2019 IEEE.Item Resource efficient allocation and RRH placement for backhaul of moving small cells(Institute of Electrical and Electronics Engineers Inc., 2019) Iftikhar, Zaeema; Jangsher, Sobia; Qureshi, Hassaan Khaliq; Aloqaily, MoayadMobile users suffer from deteriorating signal quality due to vehicle penetration losses. To solve this, small cells are deployed within the vehicles to improve the Quality of Service (QoS). These small cells called moving small cell access points (MSAPs), however, suffer from backhaul issues since they would have to send a huge amount of data to the core network. To solve the backhaul problem, cloud radio access network (CRAN) along with the millimeter wave (mmwave) can be a viable solution for moving vehicles. However, in order to realize its potential benefits, an effective remote radio head (RRH) deployment strategy and the resource-efficient allocation are needed. In this paper, we investigate the placement of RRH alongside a railway track; then, for the placed RRH, a joint time slot and power allocation problem are formulated with an objective of maximizing the resource efficiency (RE) of the MSAP backhaul network. An optimal Branch and Bound Algorithm (BnBA) is proposed for the constituted non-linear integer problem, and the effects of changing various model parameters are investigated. The simulation results show that our proposed algorithm deviates 52% of the sub-optimal result. © 2013 IEEE.