Journal of High Speed Networks - Volume 27, issue 2

Authors: Kumaraguru, Shanthi | Jebarani, M.R. Ebenezar

Article Type: Research Article

Abstract: Trust-aware routing is the significant direction for designing the secure routing protocol in Wireless Sensor Network (WSN). However, the trust-aware routing mechanism is implemented to evaluate the trustworthiness of the neighboring nodes based on the set of trust factors. Various trust-aware routing protocols are developed to route the data with minimum delay, but detecting the route with good quality poses a challenging issue in the research community. Therefore, an effective method named Sunflower Sine Cosine (SFSC)-based stacked autoencoder is designed to perform Electroencephalogram (EEG) signal classification using trust-aware routing in WSN. Moreover, the proposed SFSC algorithm incorporates Sunflower Optimization (SFO) …and Sine Cosine Algorithm (SCA) that reveals an optimal solution, which is the optimal route used to transmit the EEG signal. Initially, the trust factors are computed from the nodes simulated in the network environment, and thereby, the trust-based routing is performed to achieve EEG signal classification. The proposed SFSC-based stacked autoencoder attained better performance by selecting the optimal path based on the fitness parameters, like energy, trust, and distance. The performance of the proposed approach is analyzed using the metrics, such as sensitivity, accuracy, and specificity. The proposed approach acquires 94.708%, 94.431%, and 95.780% sensitivity, accuracy, and specificity, respectively, with 150 nodes. Show more

Keywords: Sine cosine algorithm, sunflower optimization, stacked autoencoder, electroencephalogram signal, trust aware routing

DOI: 10.3233/JHS-210654

Citation: Journal of High Speed Networks, vol. 27, no. 2, pp. 101-119, 2021

Authors: Désiré, Koné Kigninman | Dhib, Eya | Tabbane, Nabil | Asseu, Olivier

Article Type: Research Article

Abstract: Cloud gaming is an innovative model that congregates video games. The user may have different Quality-of-Experience (QoE), which is a term used to measure a user’s level of satisfaction and enjoyment for a particular service. To guarantee general satisfaction for all users with limited cloud resources, it becomes a major issue in the cloud. This paper leverages a game theory in the cloud gaming model with resource optimization to discover optimal solutions to resolve resource allocation. The Rider-based harmony search algorithm (Rider-based HSA), which is the combination of Rider optimization algorithm (ROA) and Harmony search algorithm (HSA), is proposed for …resource allocation to improve the cloud computing system’s efficiency. The fitness function is newly devised considering certain QoE parameters, which involves fairness index, Quantified experience of players (QE), and Mean Opinion Score (MOS). The proposed Rider-based HSA showed better performance compared to Potential game-based optimization algorithm, Proactive resource allocation algorithm, QoE-aware resource allocation algorithm, Distributed algorithm, and Yusen Li et al. , with maximal fairness of 0.999, maximal MOS of 0.873, and maximal QE of 1. Show more

Keywords: Cloud gaming, resource allocation, QoE, cloud computing, fairness

DOI: 10.3233/JHS-210655

Citation: Journal of High Speed Networks, vol. 27, no. 2, pp. 121-138, 2021

Authors: Shakir, Shaffath Hussain | Rajesh, A.

Article Type: Research Article

Abstract: Long Term Evolution Advanced (LTE-A) is a broadband wireless technology that supports variety of services with different data rate. In order to achieve this the evolved Node B (eNB) uses different features provided in the 3GPP standards. Features like Carrier Aggregation (CA), Multiple input and Multiple output (MIMO) and Hybrid Automatic Repeat Request (HARQ) help to increase the throughput and spectral efficiency. In this paper, a novel two-level calendar disc algorithm with HARQ is introduced at the eNB for effectively scheduling real time and non-real time traffic with different service types. The algorithm also uses a burst profile management module …that analyzes the current user profile and notifies the scheduler about the need to change in profile based on power boosting. The Calendar Disc Scheduler (CDS) is improved by adding HARQ retransmission index as a parameter in calculating the metric weight. The scheduler was tested for both adaptive and non-adaptive methods of HARQ in both synchronous and asynchronous modes. The proposed improved CDS scheduler was simulated with LTESim simulator and compared with calendar disc algorithm without HARQ improvements. Results show that the proposed scheduling method provides increased performance in terms of goodput, delay and spectral efficiency. Show more

Keywords: Long term evolution Advanced (LTE-A), Calendar Disc Scheduling (CDS), Burst profile Management (BPM), Hybrid automatic repeat request (HARQ)

DOI: 10.3233/JHS-210656

Citation: Journal of High Speed Networks, vol. 27, no. 2, pp. 139-149, 2021

Authors: Darade, Santosh Ashokrao | Akkalakshmi, M.

Article Type: Research Article

Abstract: From the recent study, it is observed that even though cloud computing grants the greatest performance in the case of storage, computing, and networking services, the Internet of Things (IoT) still suffers from high processing latency, awareness of location, and least mobility support. To address these issues, this paper integrates fog computing and Software-Defined Networking (SDN). Importantly, fog computing does the extension of computing and storing to the network edge that could minimize the latency along with mobility support. Further, this paper aims to incorporate a new optimization strategy to address the “Load balancing” problem in terms of latency minimization. …A new Thresholded-Whale Optimization Algorithm (T-WOA) is introduced for the optimal selection of load distribution coefficient (time allocation for doing a task). Finally, the performance of the proposed model is compared with other conventional models concerning latency. The simulation results prove that the SDN based T-WOA algorithm could efficiently minimize the latency and improve the Quality of Service (QoS) in Software Defined Cloud/Fog architecture. Show more

Keywords: SDN, fog networking, latency, optimization, WOA

DOI: 10.3233/JHS-210657

Citation: Journal of High Speed Networks, vol. 27, no. 2, pp. 151-167, 2021

Authors: Bhadra, Sampa Rani | Pradhan, Ashok Kumar | Biswas, Utpal

Article Type: Research Article

Abstract: For the last few decades, fiber optic cables not only replaced copper cables but also made drastic evolution in the technology to overcome the optoelectronic bandwidth mismatch. Light trail concept is such an attempt to minimize the optoelectronic bandwidth gap between actual WDM bandwidth and end user access bandwidth. A light trail is an optical bus that connects two nodes of an all optical WDM network. In this paper, we studied the concept of split light trail and proposed an algorithm namely Static Multi-Hop Split Light Trail Assignment (SMSLTA), which aims to minimize blocking probability, the number of static split …light trails assigned and also the number of network resources used, at the same time maximizing the network throughput. Our proposed algorithm works competently with the existing algorithms and generates better performance in polynomial time complexity. Show more

Keywords: Lightpath, light trail, split light trail, traffic grooming, blocking probability

DOI: 10.3233/JHS-210658

Citation: Journal of High Speed Networks, vol. 27, no. 2, pp. 169-182, 2021

Authors: Srilakshmi, V. | Anuradha, K. | Shoba Bindu, C.

Article Type: Research Article

Abstract: One of the effective text categorization methods for learning the large-scale data and the accumulated data is incremental learning. The major challenge in the incremental learning is improving the accuracy as the text document consists of numerous terms. In this research, a incremental text categorization method is developed using the proposed Spider Grasshopper Crow Optimization Algorithm based Deep Belief Neural network (SGrC-based DBN) for providing optimal text categorization results. The proposed text categorization method has four processes, such as are pre-processing, feature extraction, feature selection, text categorization, and incremental learning. Initially, the database is pre-processed and fed into vector space …model for the extraction of features. Once the features are extracted, the feature selection is carried out based on mutual information. Then, the text categorization is performed using the proposed SGrC-based DBN method, which is developed by the integration of the spider monkey optimization (SMO) with the Grasshopper Crow Optimization Algorithm (GCOA) algorithm. Finally, the incremental text categorization is performed based on the hybrid weight bounding model that includes the SGrC and Range degree and particularly, the optimal weights of the Range degree model is selected based on SGrC. The experimental result of the proposed text categorization method is performed by considering the data from the Reuter database and 20 Newsgroups database. The comparative analysis of the text categorization method is based on the performance metrics, such as precision, recall and accuracy. The proposed SGrC algorithm obtained a maximum accuracy of 0.9626, maximum precision of 0.9681 and maximum recall of 0.9600, respectively when compared with the existing incremental text categorization methods. Show more

Keywords: Text categorization, deep belief neural network, incremental learning, hybrid optimization, vector space model

DOI: 10.3233/JHS-210659

Citation: Journal of High Speed Networks, vol. 27, no. 2, pp. 183-202, 2021