An Efficient Routing Protocol for Discovering the Optimum Path in Mobile Ad Hoc Networks

Somarin, Abbas Mirzaei; Alaei, Younes; Tahernezhad, Mohammad Reza; Mohajer, Amin; Barari, Morteza

doi:10.17485/ijst/2015/v8is8/70530

Cited by 10 publications

(3 citation statements)

References 7 publications

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“…Many supervised learning algorithms such as MLP [19], CNN [20], LSTM [21,22], and unsupervised learning algorithms such as LDA [23], K-Harmonic Means [24], DBN [25] were presented for analyzing security threats. Machine learning has also been used to achieve the optimal network configuration considering resource allocation and scheduling [26], [27]. In [28], a semi-supervised learning algorithm (Q-learning) was used to dynamically adjust the appropriate number of resources for cloud computing, which has a better performance in resource management than other methods.…”

Section: Related Work and Motivationmentioning

confidence: 99%

Allocating Duplicate Copies for IoT Data in Cloud Computing based on Harmony Search Algorithm

Jahandideh

Mirzaei

2021

IETE Journal of Research

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The Internet of things (IoT) generates a plethora of data nowadays, and cloud computing has been introduced as an efficient solution to IoT data management. A cloud resource administrator usually adopts the replication strategy to guarantee the reliability of IoT data. This mechanism can significantly reduce data access time, and evidently, more replicas of data increase the data storage cost. Furthermore, the process of selecting mini clouds for replica allocation and sorting replicas in mini clouds is considered an NP-hard problem. Therefore, this paper proposes an approach based on the harmony search (HS) algorithm to allocate replicas to the IoT data in the cloud computing environment in order to mitigate the data access cost. The HS algorithm was employed in the proposed approach to determine the best location for data replication in the cloud computing environment. According to the implementation results, the proposed approach outperformed the other methods and managed to significantly decrease data access time and delay as well as energy consumption.

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Section: Related Work and Motivationmentioning

confidence: 99%

Allocating Duplicate Copies for IoT Data in Cloud Computing based on Harmony Search Algorithm

Jahandideh

Mirzaei

2021

IETE Journal of Research

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“…For this purpose, the joint problem of RA and UA are first formulated to maximize the data rate of MMTS and URFC users by considering the total system's power limitations and QoS constraints. The ruin strategy 37 is then employed to achieve the optimal UA solution via formulating the surplus energy in UAV cells and relay selection as shown in Figure 1. In this model, surplus energy can be determined as the total remaining energy for an UAV during the operational time.…”

Section: Introductionmentioning

confidence: 99%

A novel approach to QoS‐aware resource allocation in NOMA cellular HetNets using multi‐layer optimization

Mirzaei

2022

Concurrency and Computation

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The dense deployment of small cells is a key feature of the next-generation cellular networks aimed at providing the necessary capacity increase. But in such networks the problem of green networking will be of great importance, because the uncontrolled installation of too many cells may increase operational costs and emit more carbon dioxide. Nowadays, unmanned aerial vehicles (UAVs) offer an efficient approach to improve the quality, data rate, and meet the demanding performance requirements of applications in ultra-dense cellular networks. This article proposes a dynamic optimization model which minimizes the overall energy consumption of UAV cellular networks in addition to guarantying the essential coverage and capacity. The proposed model optimizes user association and power utility to meet users' QoS requirements with the highest level of energy efficiency (EE). For this purpose, the surplus energy pattern of UAVs is first mathematically formulated and then applied to calculate its ruin probability. In fact, the ruin probability denotes the vulnerability of a UAV when it runs out of energy. The ruin probability is used in the next step to efficiently connect every user to the UAVs. Also, power allocation is implemented for the applications to achieve the optimal value of the accessible network's data rate through the water-filling method. This model also performs coded routing in the multi-hop backhauls to efficiently use the existing infrastructure of the cooperative networks for coding dual-hop transmissions. The simulation results exhibit considerable network throughput and EE increase by 42% and 30%, respectively, for the proposed ruin-based energy-efficient approach in comparison with the conventional signal-to-interference/noise ratio-based schemes.

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“…However, conventional security mechanisms that provide confidentiality, integrity, and authentication are not capable of this type of protection [1] [2]. One of the major portions of the studies relevant to anonymous communications were so far related to analyzing routing algorithms with the aim of concealing actual paths from the transmitter well [3], [4]. It should be noted that, in spite of the fact that secure routing algorithms can greatly reduce path discovery attack, the enemy can gain important data via monitoring the link layer and the relevance between pairs of nodes, based on which it can identify the location and role of the base station [5] [6].…”

Section: -Introductionmentioning

confidence: 99%

A Novel Approach for Establishing Connectivity in Partitioned Mobile Sensor Networks using Beamforming Techniques

Mirzaei¹,

Zandian²

2022

jist

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Network connectivity is one of the major design issues in the context of mobile sensor networks. Due to diverse communication patterns, some nodes lying in high-traffic zones may consume more energy and eventually die out resulting in network partitioning. This phenomenon may deprive a large number of alive nodes of sending their important time critical data to the sink. The application of data caching in mobile sensor networks is exponentially increasing as a highspeed data storage layer. This paper presents a deep learning-based beamforming approach to find the optimal transmission strategies for cache-enabled backhaul networks. In the proposed scheme, the sensor nodes in isolated partitions work together to form a directional beam which significantly increases their overall communication range to reach out a distant relay node connected to the main part of the network. The proposed methodology of cooperative beamforming-based partition connectivity works efficiently if an isolated cluster gets partitioned with a favorably large number of nodes. We also present a new cross-layer method for link cost that makes a balance between the energy used by the relay. By directly adding the accessible auxiliary nodes to the set of routing links, the algorithm chooses paths which provide maximum dynamic beamforming usage for the intermediate nodes. The proposed approach is then evaluated through simulation results. The simulation results show that the proposed mechanism achieves up to 30% energy consumption reduction through beamforming as partition healing in addition to guarantee user throughput.

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An Efficient Routing Protocol for Discovering the Optimum Path in Mobile Ad Hoc Networks

Cited by 10 publications

References 7 publications

Allocating Duplicate Copies for IoT Data in Cloud Computing based on Harmony Search Algorithm

Allocating Duplicate Copies for IoT Data in Cloud Computing based on Harmony Search Algorithm

A novel approach to QoS‐aware resource allocation in NOMA cellular HetNets using multi‐layer optimization

A Novel Approach for Establishing Connectivity in Partitioned Mobile Sensor Networks using Beamforming Techniques

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