A Tool to Simulate the Transmission, Reception, and Execution of Interactive TV Applications

Neto, Manoel Carvalho Marques; Kulesza, Raoni; Rodrigues, Thiago Cagnin; Machado, Felipe A. L.; Santos, Celso A. S.

doi:10.1155/2017/1834907

Cited by 1 publication

(1 citation statement)

References 32 publications

(35 reference statements)

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“…With a combination of AR with VR, the sensory information is presented as a logical real world to its users. Earlier, majority of the applications were developed as a stand-alone solution such as simulation-based pilot training [20], evaluation of Supervisory Control and Data Acquisition (SCADA) systems [21], or inter-terrestrial image transmissions [22]. But now, the scale of such applications has improved and the majority of the applications uses a centralized server for managing information from one application and mixes it with the other for a new VR interface for the end users.…”

Section: Introductionmentioning

confidence: 99%

Osmotic computing-based service migration and resource scheduling in Mobile Augmented Reality Networks (MARN)

Sharma

Jayakody

Qaraqe

2020

Future Generation Computer Systems

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Resources and services between the servers in Mobile Augmented Reality Networks (MARN) are tedious to manage. These networks comprise users possessing Augmented Reality (AR)-Virtual Reality (VR) applications. Low latency, robustness, and tolerance are the key requirements of these networks, which can be attained by using near-user solutions such as edge computing. However, management of services and scheduling them to near-user servers in an integrated environment of edge and public/private infrastructure are complex tasks. These require an optimal solution, which can be obtained by using ''Osmotic Computing'', that has been recently proposed as a paradigm for the integration of edge and public/private cloud. This paper uses osmotic computing for effectively migrating and scheduling the services between the servers of the different layers. The paper also presents the details on various components that are used for applying osmotic computing to a network followed by core applications, types, service classification, migration, and scheduling through the rules of osmotic game formulated for its operations. The evaluations are conducted on 100,000 requests and the proposed approach shows significant performance with the probability of the error being 0.1 at 55.72% conservation of the energy and memory resources for the entire network despite the increasing number of users. The proposed approach also satisfies the conditions of the joint optimization functions presented in the system model and demonstrates that the system holds true even with varying users, thus, proving its robustness and tolerance against the number of users.

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Section: Introductionmentioning

confidence: 99%