iAgent: When AI Meets Mobile Agent

Lu, Junlin; Xiao, Wenjing; Song, Enmin; Hassan, Mohammad Mehedi; Almogren, Ahmad; Altameem, Ayman

doi:10.1109/access.2019.2926286

Cited by 8 publications

(7 citation statements)

References 42 publications

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“…It promises vital contributions to enhance life quality of humanity. Some typical applications of mobile agent technology are described as follows [22][23][24][25][26][27][28].…”

Section: Related Workmentioning

confidence: 99%

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An Improved Agent-Based AODV Routing Protocol for MANET

Nguyen¹,

Nam²,

Linh³

et al. 2021

EAI Endorsed Transactions on Industrial Networks and Intelligen

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The mobile ad-hoc network (MANET) is a special mobile network that has self-configuration and self-establish abilities to communicate conveniently. MANET is forming mobile devices such as mobile phones, personal digital assistants (PDAs), laptops, etc. As a result of the rapid, flexibility, and facilitate in communication, nowadays, MANET has revolutionized many real-life applications, ranging from smart agriculture and smart cities to forest fire detection systems, and expected to have vital contributions into the future of the Internet. However, due to the mobile nature of network nodes combined with the network architecture that without relying on central devices pre-installed such as base stations, the high-performance routing problem is one of the most significant challenges in the MANET environment. In this study, we propose a highperformance routing protocol, namely agent-based ad-hoc on-demand distance vector (A-AODV), to select the optimal route with high throughput and low latency. Through the developed routing algorithm, we explain how the suitable route with the lowest cost based on agents. To demonstrate the effectiveness of the proposed protocol, we compared A-AODV's performance with two well-known traditional protocols on NS2. Simulation results show that A-AODV improves superior performance over the traditional protocols.

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“…It promises vital contributions to enhance life quality of humanity. Some typical applications of mobile agent technology are described as follows [22][23][24][25][26][27][28].…”

Section: Related Workmentioning

confidence: 99%

“…. introduced an intelligent mobile agent framework [28], namely integrated between AI and mobile agents. A unique feature of is the self-learning ability.…”

Section: Related Workmentioning

confidence: 99%

An Improved Agent-Based AODV Routing Protocol for MANET

Nguyen¹,

Nam²,

Linh³

et al. 2021

EAI Endorsed Transactions on Industrial Networks and Intelligen

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“…A mobile agent used in the MANETs environment is small packets (probing packets) that are sent periodically between neighbouring nodes to collect information. In recent time, the solutions use mobile agents to control routing protocols more and more popular, indicated in several studies [20][21][22][23]: According to [21], the authors proposed an intelligent route planning based on mobile agents for ad hoc networks in IoT systems to make the best decision for selecting the next node in different moments. This study used the Markov Decision Process (MDP) as the underlying optimization model, which is well-known for its effectiveness to optimize decision making under uncertainty.…”

Section: Mobile Agentsmentioning

confidence: 99%

“…In [23], to improve the intelligence of the mobile agent for ad hoc networks, authors proposed a conceptual, theoretical framework named , where means intelligent, and the agent refers to the mobile agent. This study shows details of four designs of .…”

Section: Mobile Agentsmentioning

confidence: 99%

A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad Hoc Networks

Quy

Chuan

Nam

et al. 2021

Int. J. Interact. Mob. Technol.

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This paper presents a modification of a well-known routing protocol, namely Ad hoc On-Demand Distance Vector, as a solution to improve the performance of mobile ad hoc networks. We adapted the mobile agent technology as to novel metrics for routing in those networks. The metric is a function of the loss rate, the bandwidth and the end-to-end delay of the link. Indeed, we established a new tunable parameter to obtain a tradeoff between throughput and delay when computing the new metric. As a result, any routing protocol using this metric can al-ways choose a high-throughput and low-delay path between a source and a destination. Hence, the achievable performance of the mobile ad hoc networks has been improved remarkably with our modified routing protocol,

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“…In [26] Agent Based Call Scheduling Technique with Optimum Resource Utilization in Cellular Controlled Short-Range Communication (CCSRC) Network is proposed which concentrates on scheduling the calls in CCSRC networks by minimizing the energy consumption of mobile nodes and increasing the spectrum utilization efficiency of the network. In [27], an attempt is being made to improve the mobile agent-based system by using Artificial Intelligence (AI) to improve load balancing across networks in energy efficient manner in wireless sensor networks. Mobile agents have recently been used for dynamic channel acquisition in mobile cloud computing, which can dynamically choose users to transmit data based on queue backlog and channel statistics [28].…”

Section: Resource Management Using Mobile Agentsmentioning

confidence: 99%

Dynamic QoS Management for Interactive Multimedia in Integrated 4G/5G Networks

Keshav¹,

Pradhan²,

Srinivas³

et al. 2021

ICST Transactions on Mobile Communications and Applications

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INTRODUCTION: Emerging interactive multimedia applications such as VR have some key requirements that communication medium must full fill in order to have a smooth interactive experience. These requirements include higher uplink and downlink throughput requirement, low latency, and consistent throughput even at the cell edge. Present day 4G/5G Network faces a lack of resource availability for highly sophisticated applications like interactive multimedia. While 4G/5G networks do have a QoS mechanism to handle multiple varieties of traffic requirements, they are passive. At best, initial negotiated QoS are changed on a reactive basis. OBJECTIVES:This work proposes a dynamic QoS management scheme so that the overall necessary resource allocation for interactive multimedia and non-interactive applications can occur. METHODS: The scheme uses mobile agents which can efficiently predict possible disruption in QoS and help both server and users to adapt to changing network situation. This way user can be notified of an expected or estimated service quality change in advance, timely adaptation is possible. use this information to for efficient QoS negotiation and re-negotiation. RESULTS: The developed scheme has been tested with different sizes of the 4G/5G networks with several virtual reality users along with other background loads of applications. CONCLUSION: Results are quite encouraging and the system is practically implementable.

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iAgent: When AI Meets Mobile Agent

Cited by 8 publications

References 42 publications

An Improved Agent-Based AODV Routing Protocol for MANET

An Improved Agent-Based AODV Routing Protocol for MANET

A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad Hoc Networks

Dynamic QoS Management for Interactive Multimedia in Integrated 4G/5G Networks

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