scholarly journals Latency-Aware Power Management in Software-Defined Radios

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Nicolas Malm ◽  
Kalle Ruttik ◽  
Olav Tirkkonen
Keyword(s):  
Cloud Computing ◽  
Software Defined Radio ◽  
Cloud Service ◽  
Cellular Communication ◽  
Network Interface ◽  
Clock Frequency ◽  
Computing Platforms ◽  
4G Lte ◽  
The Relationship ◽  
Potential Remedy

Cloud computing provides benefits in terms of equipment consolidation and power savings from higher utilization for virtualizable software. Cellular communication software faces challenges in cloud computing platforms. BSs create a specific load profile that differs from traditional cloud service loads. Cellular communication system implementations have real-time deadlines with fixed, periodic latency requirements. In this paper, we assess the suitability of an unmodified Ubuntu Linux OS running on a commodity server to operate latency-critical software using a 4G LTE BS software-defined radio implementation. Scaling of the CPU clock frequency is shown to be feasible without excessive impact on the platform’s ability to meet the 4 ms processing delay requirement imposed by the LTE standard. Measurements show the relationship between the processor’s operating frequency and the number of missed subframe processing deadlines to be nonlinear. The results obtained also indicate that a high computational capacity does not suffice to ensure satisfactory operation since fronthaul processing overhead can limit achievable performance. Use of offload-capable network interface cards is studied as a potential remedy.

scholarly journals Dear Cloud, I Think We Have Trust Issues: Cloud Computing Contracts and Trust

2020 ◽  
pp. 21-42
Author(s):  
Theo Lynn
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Standard Form ◽  
Cloud Service ◽  
Contract Law ◽  
Cloud Service Provider ◽  
Internet Users ◽  
Cloud Service Providers ◽  
The Relationship ◽  
Dominant Paradigm

Abstract Cloud computing is the dominant paradigm in modern computing, used by billions of Internet users worldwide. It is a market dominated by a small number of hyperscale cloud service providers. The overwhelming majority of cloud customers agree to standard form click-wrap contracts, with no opportunity to negotiate specific terms and conditions. Few cloud customers read the contracts that they agree to. It is clear that contracts in cloud computing are primarily an instrument of control benefiting one side, the cloud service provider. This chapter provides an introduction to the relationship between psychological trust, contracts and contract law. It also offers an overview of the key contract law issues that arise in cloud computing and introduces some emerging paradigms in cloud computing and contracts.

Architecture and System Design for Marine Cloud Computing Assets

2020 ◽  
Vol 63 (6) ◽  
pp. 927-941 ◽  
Author(s):  
A A Periola ◽  
A A Alonge ◽  
K A Ogudo
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Low Cost ◽  
Cloud Service ◽  
Artificial Reefs ◽  
Free Cooling ◽  
Acquisition Costs ◽  
Computing Platforms ◽  
Power Usage Effectiveness ◽  
Data Centres

Abstract The Ocean provides benefits of free cooling for cloud computing platforms. However, the use of the ocean for hosting cloud platforms needs to consider three challenges. The first challenge is identifying suitable underwater locations for siting underwater data centres. The second is designing a low-cost method for acquiring underwater data centres. The third is designing a mechanism ensuring that the use of the ocean for hosting data centres is scalable. This paper proposes the intelligent marine compute locator (IMCL) to identify suitable locations for siting underwater data centres. The proposed IMCL determines the specific heat capacity of different ocean locations at multiple epochs. In addition, the conversion of end-of-life vessels into artificial reefs that host open-source disaggregated hardware computing payload is proposed to reduce acquisition costs. The use of disaggregated architecture enables multiple cloud service providers to use limited ocean locations. The formulated metrics are the power usage effectiveness (PUE) and ocean space utilization (OSU). Simulations show that the use of disaggregated design architecture instead of non-disaggregated architecture (existing mechanism) enhances the PUE and OSU by 4.4 and 16.4% on average, respectively.

Cognitive Radio Network-Based Design and Security Challenges in 5G Communication

2020 ◽  
pp. 221-241 ◽  
Author(s):  
Arvind Dhaka ◽  
Amita Nandal ◽  
Rahul Dixit
Keyword(s):  
Cloud Computing ◽  
Cognitive Radio ◽  
Mobile Networks ◽  
Software Defined Radio ◽  
General Purpose ◽  
Security Issues ◽  
Computing Platform ◽  
Security Challenges ◽  
Signal Processing Algorithms ◽  
Computing Platforms

This chapter deals with the main development challenges of 5G network. The 5G terminals can be made as reconfigurable multimode and cognitive radio enabled. Such networks will have software defined radio modulation schemes. The 5G mobile networks will focus on the development of the user terminals where the terminals will have access to different wireless technologies at the same time and will combine different flows from different technologies. It is beneficial to deploy cloud-computing platforms running on general-purpose hardware, leading to a cloud-RAN system. This chapter is focused on the challenges and benefits of implementing reconfigurable signal processing algorithms on a cloud-computing platform and address various security issues with cognitive radio networks.

Mis-Configuration Investigation for the Cloud Computing Based on the Fuzzy Pattern Recognition

2013 ◽  
Vol 336-338 ◽  
pp. 2369-2375
Author(s):  
Bin Wu ◽  
Ji Tao Ma ◽  
Ping Wu
Keyword(s):  
Pattern Recognition ◽  
Cloud Computing ◽  
Service Management ◽  
Cloud Service ◽  
Simulation Environment ◽  
Fuzzy Pattern Recognition ◽  
Fuzzy Pattern ◽  
Important Field ◽  
The Common ◽  
The Relationship

The mis-configuration investigation is an important field in the security of cloud computing. However, the common method of investigating mis-configuration is a post-processing way. In order to find errors in the process of the cloud service management timely, we analyze the relationship between indicators of the cloud computing and locations of configuration items in this paper. According to this relationship, we construct a solution model based on the fuzzy pattern recognition. The lattice degree of nearness is used to determined locations of the mis-configuration. We further test the validity and accuracy of the model under the cloud simulation environment. The results show that the model is more effective and accurate to find the location of the mis-configuration rapidly.

scholarly journals Towards Hardware OpenGL Support in Cloud Computing

2021 ◽  
Author(s):  
Evgeny Yurievich Denisov ◽  
Irina Aleksandrovna Kalugina
Keyword(s):  
Cloud Computing ◽  
Computer Graphics ◽  
Virtual Machines ◽  
Service Providers ◽  
Distributed Processing ◽  
Cloud Service ◽  
Computing Services ◽  
Lighting Simulation ◽  
Computing Platforms ◽  
Simulation Systems

Modern realistic computer graphics applications, such as physically accurate lighting simulation systems, require a lot of computer power for images generation. Usage of the resources of cloud computing platforms for such calculations allows to avoid additional expenses for purchase and maintenance of own computer farms. However often such simulation systems use OpenGL for 3D images display, for example during scene preparation and modification. Since cloud-based virtual machines had only software (that is, slow) OpenGL display support, it was not convenient for the users to work with their habitual computer graphics applications in such environments, and typical workflow was to prepare all data on local computer and then execute simulation in the cloud service (usually using distributed processing). Recently several cloud computer service providers started to suggest users the option of hardware (GPU-based) OpenGL support in their cloud virtual machines. This article is devoted to the investigation of hardware OpenGL display options, suggested by various providers of cloud computing services, and their comparison. Available types of hardware GPU were checked and compared, along with the conditions for their usage.

Cloud Computing

2012 ◽  
pp. 191-207 ◽  
Author(s):  
Shantanu Pal
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Effective Means ◽  
Cloud Service ◽  
Security And Privacy ◽  
Cloud Infrastructure ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Security Issues ◽  
Computing Platforms

In a cloud ecosystem, most of the data and software that users use reside on the remote server(s), which brings some new challenges for the system, especially security and privacy. At present, these security threats and attacks are the greatest concern for the service providers towards delivering a more secure cloud infrastructure. One of the major concerns is data security, implemented by the most effective means possible and the protection of stored data from unauthorized users and hackers. When considering these security issues, trust is one of the most important means to improve the system’s security and enable interoperability of current heterogeneous cloud computing platforms. The objective of this chapter is to discuss and understand the basic security and privacy challenges of a cloud computing environment as the security of cloud computing is the greatest challenge for delivering a safer cloud environment for both the service providers and the service customers. With this in mind, this chapter will introduce the risks and possible attacks in a cloud computing environment. The major goal is to specify the security risks and attacks and consider trust of cloud service users for delivering a safer and innovation business model.

Multi-Dimensional Performance Optimization in Cloud Computing

2017 ◽  
Vol 14 (1) ◽  
pp. 335-340
Author(s):  
Yu Shengji ◽  
Xiang Yanping
Keyword(s):  
Cloud Computing ◽  
Performance Optimization ◽  
Service Providers ◽  
Cloud Service ◽  
Function Technique ◽  
Service Time Distribution ◽  
Network Resource ◽  
Optimal Network ◽  
Multi Agent ◽  
Computing Platforms

The challenge of multi-dimensional performance optimization has been extensively addressed in the literature based on deterministic parameters. Since resources in Cloud Computing platforms are geographically separated and heterogeneous, it is rather difficult to apply a uniform distribution algorithm for achieving various optimization goals. Based on the analysis of cloud service performance measures, this paper proposes an approach for optimal network resource distribution managed by the multi-agent system (MAS), which is aimed to satisfy both the users’ and the service providers’ requirements. Moreover, a communication algorithm that uses the universal generating function technique is proposed to obtain the service time distribution efficiently.

scholarly journals Proposed Digital Evidence Sharing and Preserving Mechanism in Cloud Computing Environments: اقتراح آلية لتبادل الأدلة الرقمية والحفاظ عليها في بيئات الحوسبة السحابية

2021 ◽  
Vol 5 (3) ◽  
pp. 111-92
Author(s):  
Waseem Mohammad Maamoun Al-Sbaiti, Maher Abdulrahman Abbas,  Waseem Mohammad Maamoun Al-Sbaiti, Maher Abdulrahman Abbas, 
Keyword(s):  
Cloud Computing ◽  
Cloud Service ◽  
Digital Evidence ◽  
Cloud Provider ◽  
User Privacy ◽  
Forensic Evidence ◽  
Robust Model ◽  
Digital Surveillance ◽  
Proposed Model ◽  
Computing Platforms

Investigations and digital evidence have become an important and critical discipline that has made many researchers devote vigorous efforts to developing digital surveillance and investigation mechanisms, especially after the great expansion of the technical infrastructure on cloud computing platforms, which added more challenges to digital investigation. So far, no robust model has been found for preserving and exchanging digital evidence between clouds and users without this model causing a breach of user privacy or affecting performance. Most of the current studies on digital evidence exchange mechanisms rely at one stage of the exchange or evidence formation process on the CSP, which allows the cloud provider (or a malicious employee within the cloud provider) to manipulate the evidence or data. This research will present a proposal for a mechanism for sharing and preserving digital evidence between the cloud parties, taking into account the performance in the major cloud computing models (IaaS, PaaS, SaaS), and how this model can achieve evidence integrity and a less level of interference in the privacy of the user as well as the cloud service provider considering that may be more than one party accused as forgery. To achieve this, we have selected some digital evidence that digital investigators can rely on as digital forensic evidence in cases related to information crimes as a sample that can be exchanged and verified that none of them has tampered with this evidence, especially since cloud environments may go beyond having a single cloud that performs the service and thus there are several clouds involved in forming evidence, then we tested this mechanism by applying the SHA-2 Hashing process to digital evidence, then encrypting the output with the Elliptic Curve Cryptography algorithm and measuring the time needed to exchange and verify the evidence. We will compare the proposed model with models in previous studies to illustrate how the proposed model overcame the problem of relying on one party to form the evidence with the least impact for all parties on the level of performance or privacy, and how distributed SHA-2 hashing values proved its effectiveness in the inability of any party to deny the evidence or tamer it.

scholarly journals General Collective Intelligence and the Cloud

2021 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Cloud Computing ◽  
Collective Intelligence ◽  
Cloud Service ◽  
Cloud Services ◽  
Cognitive Computing ◽  
Computing Platform ◽  
On Demand ◽  
Exponential Increase ◽  
Functional Models ◽  
Computing Platforms

The resources that can be made available on-demand through cloud computing are continually increasing. One potential addition is General Collective Intelligence or GCI, which has been defined as a platform that combines individuals into a single intelligence with the potential for exponentially greater general problem-solving ability (intelligence) than any individual. The concept of a cognitive computing platform involves leveraging GCI to orchestrate cooperation between any entities that are required in order to create the capacity to maximize any collective outcome targeted. Rather than executing programming code, a cognitive computing platform must execute functional models in which each of the functional operations composing that model is implemented in some programming language. All services that run on the cloud, as well as the cloud itself, can potentially be offered as cognitive computing platforms. Where current cloud computing limits customers to a particular cloud service vendor, cloud computing as a cognitive computing platform has the potential to completely decouple users from any such dependencies, while at the same time creating the potential for an exponential increase in demand for cloud services from those vendors that participate by decoupling their services in this way.

scholarly journals A Survey on Improving QoS in Service Level Agreement for Cloud Computing Environment

2021 ◽  
Vol 15 (21) ◽  
pp. 119
Author(s):  
Afaf Edinat ◽  
Rizik M. H. Al-Sayyed ◽  
Amjad Hudaib
Keyword(s):  
Cloud Computing ◽  
Learning Process ◽  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Shared Services ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
The Relationship

Cloud computing is considered one of the most important techniques in the field of distributed computing which contributes to maintain increased scalability and flexibility in computer processing. This is achieved because it, using the Internet, provides different resources and shared services with minimum costs. Cloud service providers (CSPs) offer many different services to their customers, where the customers’ needs are met seeking the highest levels of quality at the lowest considerate prices. The relationship between CSPs and customers must be determined in a formal agreement, and to ensure how the QoS between them will be fulfilled, a clear Service Level Agreement (SLA) must be called for. Several previously-proposed models used in the literature to improve the QoS in the SLA for cloud computing and to face many of the challenges in the SLA are reviewed in this paper. We also addressed the challenges that are related to the violations of SLAs, and how overcoming them will enhance customers’ satisfaction. Furthermore, we proposed a model based on Deep Reinforcement Learning (DRL) and an enhanced DRL agent (EDRLA). In this model, and by optimizing the learning process in EDRLA, proposed agents would be able to have optimal CSPs by improving the learning process in EDRLA. This improvement will be reflected in the agent's performance and considerably affect it, especially in identifying cloud computing requirements based on the QoS metrics.

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