Technical analysis of content placement algorithms for content delivery network in cloud

<p>Content placement algorithm is an integral part of the cloud-based content de-livery network. They are responsible for selecting a precise content to be re-posited over the surrogate servers distributed over a geographical region. Although various works are being already carried out in this sector, there are loopholes connected to most of the work, which doesn't have much disclosure. It is already known that quality of service, quality of experience, and the cost is always an essential objective targeting to be improved in existing work. Still, there are various other aspects and underlying reasons which are equally important from the design aspect. Therefore, this paper contributes towards reviewing the existing approaches of content placement algorithm over cloud-based content delivery network targeting to explore open-end re-search issues.</p>

A Node Placement Algorithm Utilizing Mobile Nodes in WSN and IoT Networks

The operation of the Internet of Things (IoT) networks and Wireless Sensor Networks (WSN) is often disrupted by a number of problems, such as path disconnections, network segmentation, node faults, and security attacks. A method that gains momentum in resolving some of those issues is the use of mobile nodes or nodes deployed by mobile robots. The use of mobile elements essentially increases the resources and the capacity of the network. In this work, we present a Node Placement Algorithm with two variations, which utilizes mobile nodes for the creation of alternative paths from source to sink. The first variation employs mobile nodes that create locally-significant alternative paths leading to the sink. The second variation employs mobile nodes that create completely individual (disjoint) paths to the sink. We then extend the local variation of the algorithm by also accounting for the energy levels of the nodes as a contributing factor regarding the creation of alternative paths. We offer both a high-level description of the concept and also detailed algorithmic solutions. The evaluation of the solutions was performed in a case study of resolving congestion in the network. Results have shown that the proposed algorithms can significantly contribute to the alleviation of the problem of congestion in IoT and WSNs and can easily be used for other types of network problems.

A Comparative Study of Services Placement Algorithms in Future Networks: دراسة مقارنة لخوارزميّات توضيع الخدمات في الشّبكات المستقبليّة

The study aimed to analyze and compare several algorithms in the context of networks services placement, and then proposed a self-organized dynamic heuristic algorithm adaptable to continually changing network conditions in order to achieve the ideal placement of services replicas in future networks. It is known that future networks demand a high degree of self-organization to keep pace with ongoing changes while maintaining performance optimized. One of the important challenges in this context is the services placement problem. Service placement issue refers to the selection of the most appropriate network node for hosting a service. The ideal placement of services replicas reduces the cost of serving customers, improves connectivity between clients and servers as well as the use of available resources. The study summarized the results of qualitative comparison between several placement algorithms and refers to the most important requirements to be taken into account when implementing the placement algorithm. Generally, each service has its own placement technique, and the action taken by a specific service may affect other services decisions and force them to adapt. There is an urgent need to a management service for managing services replicas to make the optimal placement decision. This service should work in a distributed manner and does not require comprehensive knowledge about the network. It is also characterized by its ability to adapt to changing network conditions in terms of load and topology. Other services coordinate with the management service about replicating or migrating actions, thus services will be offered at a minimized cost.

3D Placement of a New Tethered UAV to UAV Relay System for Coverage Maximization

In this paper, a new relay system that uses the UAV as a relay station between the tethered UAV and ground user (TU2U2G) is proposed. The TU2U2G system replaces the base station (BS) in the cellular system with a tethered UAV (TUAV). The TUAV is a UAV that receives power over a cable from a ground control station. It has advantages of high and variable altitude up to (100m) compared to BS. In addition, it overcomes the UAV drawback of the batteries' limited capacity. After that, a 3D placement Algorithm of the UAV as a relay station in the TU2U2G system is proposed. It is presented to maximize the coverage by jointly optimizing the transmitting power and relaying distance. The TU2U2G system shows better results than the traditional cellular system in terms of optimum UAV height, maximum coverage radius, and maximum distance between BS and UAV.

ARPA: An autonomous renderer placement algorithm in distributed multimedia fog networks with delay guarantees

Multimedia cloud computing has emerged as a popular paradigm for the support of delay-intolerable immersive multimedia applications with high-end three-dimensional rendering. To that end, fog computing offers distributed computational offloading solutions, by positioning rendering servers in close proximity to end users promising in this way continuous service provision, that is otherwise not easily attainable under the strictly centralized cloud-only model. Yet, in order to alleviate the multimedia providers from unnecessary capital expenditure, a strategic placement approach of the servers at the fog layer must be implemented, that can effectively cope both with the network dynamics and the overall imposed deployment cost, and still adhere to the delay bounds set forth by the multimedia application. In this paper, we formally formulate the problem as a facility location problem using constrained optimization over a finite time horizon. We then theoretically analyze the minimum acceptable conditions necessary for a decentralized location of the servers, utilizing solely local information around their immediate neighborhood, that iteratively leads to better solutions. Based on the analysis, we propose a distributed algorithm, namely the Autonomous Renderer Placement Algorithm (ARPA), to address it. ARPA employs localized service relocation to shift the placement according to simple rules that designate elastic migration, replication, and complementary consolidation of the underlying renderers. Simulation results under diversified deployment scenarios, as well as trace-driven comparisons against other approaches, testify to ARPA's accountability in obeying the delay limits and fast converge in finite time slots to a placement solution that both outperforms the baseline alternatives and is close to the optimal one, rendering it suitable for scaling up and down to meet the current demands of the offered multimedia applications.

Comparative Analysis of Different Data Replication Strategies in Cloud Environment

In this paper, we performed a comparative study of the different data replication strategies such as Adaptive Data Replication Strategy (ADRS), Dynamic Cost Aware Re-Replication and Rebalancing Strategy (DCR2S) and Efficient Placement Algorithm (EPA) in the cloud environment. The implementation of these three techniques is done in JAVA and the performance analysis is conducted to study the performance of those replication techniques by various parameters. The parameters used for the performance analysis of these three techniques are Load Variance, Response Time, Probability of File Availability, System Byte Effective Rate (SBER), Latency, and Fault Ratio. From the analysis, it is evaluated that by varying the number of file replicas, it shows deviations in the outcomes of these parameters. The comparative results were also analyzed.