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.Ĭloud computing has seen rapid growth and environments are now providing multiple physical servers with several virtual machines running on those servers. This way user can be notified of an expected or estimated service quality change in advance, timely adaptation is possible. 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 helpboth server and users to adapt to changing network situation. While 4G/5G networks do have a QoS mechanism to handle multiple varieties of traffic requirements, they are passive. Present day 4G/5G Network faces a lack of resource availability for highly sophisticated applications like interactive multimedia. These requirements include higher uplink and downlink throughput requirement, low latency, and consistent throughput even at the cell edge.
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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.
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