2024-03-29T10:05:03+04:30 http://ijict.itrc.ac.ir/browse.php?mag_id=9&slc_lang=en&sid=1
9-71 2024-03-29 10.1002
International Journal of Information and Communication Technology Research 2251-6107 2783-4425 doi 2016 8 1 A Novel Adaptive Router Placement Scheme in Hybrid Wireless Optical Access Network Fariborz Mousavi Madani A typical wireless optical network takes advantage of passive optical network (PON) architecture in the back-end for last-mile broad-band connectivity combined with wireless mesh network at the front-end to provide high-quality cost-effective Internet access to end users. Wireless gateway routers collect upstream traffic from enduser devices within their transmission range and route them toward a nearby optical network unit (ONU) station and vice versa in the downstream direction. A major objectives of planning wireless optical networks is to place ONUs and wireless routers (WRs) in such a way to fully cover all end-users with minimum deployment cost while ensuring some quality metrics, such as delay or throughput. Computational complexity of mathematical formulations presented in previous works, restrains from scaling the network size and user population in accordance with the realistic circumstances. In this paper, we address this issue by introducing a novel adaptive segmentation scheme to offload the problem complexity without sacrificing the optimality of solution. Extensive numerical simulations verified the applicability of our approach to large-scale networks. FiWi network WOBAN Router placement 2016 3 01 1 8 http://ijict.itrc.ac.ir/article-1-71-en.pdf
9-72 2024-03-29 10.1002
International Journal of Information and Communication Technology Research 2251-6107 2783-4425 doi 2016 8 1 Ensemble Link Predictor for Heterogeneous Complex Networks Hadi Shakibian Nasrollah Moghadam Charkari Saeed Jalili Link prediction in complex networks aims to explore similarities between node pairs. Recently, link prediction has been considered in the presence of network heterogeneity which makes the majority of the homogeneous link prediction approaches infeasible. A meta-structure, known as meta-path, has been proposed to explore such networks. Generating good meta-paths and selecting the best of them introduce some new challenges to link prediction problem. In this paper, a new ensemble-based link prediction approach is proposed in heterogeneous complex networks. This approach consists of three steps: (i) a set of meta-paths are selected such that each of them represents a different semantic between the target node pairs; (ii) a feature vector is extracted for each node pair using each meta-path; (iii) an ensemble of learners would be established on different feature sets. The final link predictor is obtained after the ensemble aggregation. The results on DBLP network show that the proposed approach has more accurate predictions than a single meta-path based link predictor. Heterogeneous Complex Networks Link Prediction Meta-path 2016 3 01 9 14 http://ijict.itrc.ac.ir/article-1-72-en.pdf
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International Journal of Information and Communication Technology Research 2251-6107 2783-4425 doi 2016 8 1 SDTE: Software Defined Traffic Engineering for Improving Data Center Network Utilization Marzieh Khoshbakht Mohammad Mahdi Tajiki Behzad Akbari In recent years, several topologies with multiple-path between each pairs of end hosts for data center (DC) networks have been proposed. However, the path diversity is shown to be not enough to improve the network performance. Researches on the DC network measurements have shown that congestion occurs even when the average utilization of links is low, which means that some of the links are over-utilized while others are underutilized and have a considerable available bandwidth. Therefore, traffic engineering (TE) is necessary for proper distribution of the network load as well as exploiting the path diversity that is provided by new topologies. Current Equal Cost Multi Path (ECMP) based approaches are not efficient in lots of cases because numerous big flows may collide on the same path. The centralized solutions depend on the ability to predict the traffic pattern, which is not effective for unpredictable traffic patterns of data centers. In this paper, SDTE, an online software defined TE approach is proposed for cloud data centers. The proposed system does not depend on the ability to predict traffic pattern or the size of flows. SDTE exploits the PEFT routing algorithm to assign weights to links. SDTE is implemented within the OpenFlow framework. The evaluation shows that SDTE performs close to the optimal routing (average deviation is about 7%). Software Defined Networking Data Center Routing Multipath Routing Traffic Engineering Cloud Computing OpenFlow 2016 3 01 15 24 http://ijict.itrc.ac.ir/article-1-73-en.pdf
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International Journal of Information and Communication Technology Research 2251-6107 2783-4425 doi 2016 8 1 A Novel Trust Evaluation Model Using Graph Clustering Approach Mohammad Ali Mahmoodyar Mohammad Jafar Tarokh This is the time of rapidly development of electronic relationships between the users of a social network. Any entity in e-interactions has to make decision about trust/distrust to others with respect to the data available on the network. Also the lack of significant information about the entities becomes a challenge that any trust evaluation model has to deals with it. In this paper, a model for evaluation trust with respect to the users’ feedbacks is proposed. The model, is based on a unique generated trusted graph which is the result of applying a proposed initial trust value metric. Also, the communities consisting the network is detected using Markov Clustering Algorithm (MCL). This paper also presents a categorical -based approach for trust evaluation. The proposed model has been compared to another trust metric which is proposed by another paper and. The results, which achieved using Normalized Root Mean Squared Error (NRMSE), show the effects of proposed initial trust value and proposed final trust rate on the final trust evaluations . By more affecting the final trust rate, the model goes more closely to the basis trust metric used for comparing results. Trusted Graph User Reputation Graph Clustering Markov Clustering Algorithm (MCL) 2016 3 01 25 31 http://ijict.itrc.ac.ir/article-1-74-en.pdf
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International Journal of Information and Communication Technology Research 2251-6107 2783-4425 doi 2016 8 1 Detecting Flood-based Attacks against SIP Proxy Servers and Clients using Engineered Feature Sets Hassan Asgharian Ahmad Akbari Bijan Raahemi Session Initiation Protocol (SIP) is the main signaling protocol of the next generation networks. The security issues of SIP-based entities (i.e. proxy servers and clients) have a direct impact on the perceived quality of experience of end users in multimedia sessions. In this paper, our focus is on the S IP flooding attacks including denial of service and distributed denial of service attacks. After classifying various types of SIP attacks based on their sources, we extract four feature sets based on the specification of its attack group, as well as the normal behavior of the SIP state machine specified in RFC 3261. We then minimize the number of derived features in each set to reduce the computational complexity of our proposed approach. This facilitates employing the engineered feature sets in embedded S IP-based devices such as cell phones and smart TVs. We evaluate the performance of the proposed feature sets in detecting SIP attack sequence. For this, we design and implement a real test-bed for SIP-based services to generate normal and attack traffics. The experimental results confirm that the engineered feature sets perform well in terms of detection accuracy and false alarm rates in classifying benign and anomaly traffic in various attack scenarios. SIP Security SIP Feature Set SIP intrusion detection system Application Layer DoS Attack (DDoS) SIP state machine VoIP IDS NGN and IMS Security 2016 3 01 33 41 http://ijict.itrc.ac.ir/article-1-75-en.pdf
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International Journal of Information and Communication Technology Research 2251-6107 2783-4425 doi 2016 8 1 A Priority-based Fast Optimal Computation Offloading Planner for Mobile Cloud Computing Mohammad Goudarzi Zeinab Movahedi Guy Pujolle Today's advances of mobile technologies in both hardware and software have pushed the vast utilization of mobile devices for diverse purposes. Along with this progress, today’s mobile devices are expected to perform various types of applications. However, the energy challenge of mobile devices along with their limited computation power act as a barrier. To address this deficiency, mobile cloud computing has been proposed in which cloud resources are used to extend mobile devices’ capabilities. However, due to varying conditions of wireless channel in terms of connectivity and bandwidth, an online offloading mechanism is required which may lead to high decision time and energy. To address this challenge, we propose a priority-based fast computation offloading mechanism which finds the optimal offloading solution based on a modified branch-and-bound algorithm. Results of intensive simulation and testbed experiments demonstrated that our proposal can outperform all existing optimal counterparts in terms of energy consumption and execution time. Mobile Cloud Computing Computation Offloading Optimal Partitioning 2016 3 01 43 49 http://ijict.itrc.ac.ir/article-1-76-en.pdf
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International Journal of Information and Communication Technology Research 2251-6107 2783-4425 doi 2016 8 1 A Pareto-based Optimizer for Workflow Scheduling in Cloud Computing Environment Azade Khalili Seyed Morteza Babamir A scheduling algorithm in cloud computing environment is in charge of assigning tasks of a workflow to cloud’s virtual machines (VMs) so that the workflow completion time is minimized. Due to the heterogeneity and dynamicity of VMs and diversity of tasks size, workflow scheduling is confronted with a huge permutation space and is known as an NP-complete problem; therefore, heuristic algorithms are used to reach an optimal scheduling. While the single-objective optimization i.e., minimizing completion time, proposes the workflow scheduling as a NP-complete problem, multi-objective optimization for the scheduling problem is confronted with a more permutation space. In our pre vious work, we considered single-objective optimization (minimizing the workflow completion time) using Particle Swarm Optimization (PSO) algorithm. The current study aims to present a multi -objective optimizer for conflicting objectives using Gray Wolves Optimizer (GWO) where dependencies exist between workflow tasks. We applied our method to Epigenomics (balanced) and Montage (imbalanced) workflows and compared our results with those of the SPEA2 algorithm based on parameters of Attention Quotient, Max Extension, and Remoteness Dispersal. Cloud computing Task scheduling Grey Wolf Optimizer Multi -objective optimization Pareto front Strength Pareto Evolutionary Algorithm2 (SPEA2) 2016 3 01 51 59 http://ijict.itrc.ac.ir/article-1-77-en.pdf