Edge computing has transformed machine learning by using computing closer to the data sources, thereby reducing latency. The ever-increasing volume of data has necessitated forming clusters of edge devices, possibly w...
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In this paper, we propose a distributed and interactive Plug-in Electric Vehicle (PEV) charging scheduling approach, which is also combined with an optimal pricing strategy. This method tackles challenges such as fluc...
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Complex interactions within microservice architectures obfuscate the implications of individual services to high-level requirements. This becomes even more grave for multi-tenant and multi-vendor scenarios, like Edge ...
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ISBN:
(纸本)9798331539580
Complex interactions within microservice architectures obfuscate the implications of individual services to high-level requirements. This becomes even more grave for multi-tenant and multi-vendor scenarios, like Edge computing, where different stakeholders might specify opposing Service Level Objectives (SLOs), e.g., minimizing both energy consumption and response time. To avoid contradictions within SLOs and to infer how SLOs can be fulfilled, this paper presents a methodology that diffuses high-level SLOs into multiple lower levels of SLOs and parameter assignments. Thus, it becomes clear how individual sub-processes contribute to high-level SLOs, and how these must be configured to foster their fulfillment. We evaluated our methodology for several microservice pipelines, where the challenge is to ensure multiple high-level SLOs (e.g., customer satisfaction) by finding and constraining all influential factors. The results show that by inferring multiple layers of lower-level constraints, we can fulfill high-level SLOs up to 100%. Notably, we could extract that the restrictiveness of low-level SLOs and the occurrence of conflicts have a severe impact on SLO fulfillment.
The Internet of Things (loT) has become an important aspect in various domains such as smart cities, healthcare and industrial revolution. There are various concerns of energy consumption ever since the widespread of ...
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distributed tracing has become a fundamental tool for diagnosing performance issues in the cloud by recording causally ordered, end-to-end workflows of request executions. However, tracing workloads in production can ...
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ISBN:
(纸本)9798331528690;9798331528706
distributed tracing has become a fundamental tool for diagnosing performance issues in the cloud by recording causally ordered, end-to-end workflows of request executions. However, tracing workloads in production can introduce significant overheads due to the extensive instrumentation needed for identifying performance variations. This paper addresses the trade-off between the cost of tracing and the utility of the "spans" within that trace through Astraea, an online probabilistic distributed tracing system. Astraea is based on our technique that combines online Bayesian learning and multi-armed bandit frameworks. This formulation enables Astraea to effectively steer tracing towards the useful instrumentation needed for accurate performance diagnosis. Astraea localizes performance variations using only 20-35% of available instrumentation, markedly reducing tracing overhead, storage, compute costs, and trace analysis time.
The exponential growth of distributed cloud systems necessitates an intelligent form of workload management that ensures optimum performance, scalability, and reliability. Traditional approaches based on static or heu...
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distributed applications running on virtualizationbased systems and cloud computing have become popular solutions, allowing developers to focus on application logic rather than dealing with the complexities of distrib...
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ISBN:
(纸本)9798350308297
distributed applications running on virtualizationbased systems and cloud computing have become popular solutions, allowing developers to focus on application logic rather than dealing with the complexities of distributedsystems. However, these applications often become increasingly complex, presenting multiple management challenges. To address this issue, software visualization approaches offer valuable solutions by providing real-time insights into resources and their functionalities, offering a comprehensive overview. This study aims to analyze and evaluate existing software visualization tools for distributed applications on the Kubernetes platform. The objective is to comprehensively examine these tools' features, capabilities, and limitations to understand their effectiveness in visualizing complex distributedsystems. Our findings provide valuable insights into the strengths and weaknesses of the available visualization tools, enabling researchers and practitioners to make informed decisions and advancements in software visualization for distributed applications on the Kubernetes platform. Our research identified eight Kubernetes visualization tools, which were examined and compared based on relevant characteristics related to distributed applications and software visualization standards. However, it is worth noting that despite the excellent work done by the community in establishing these first proposals, these tools currently only support, on average, a visualization of 9% of the total resource types available, as mentioned in the official documentation. Therefore, we propose guidelines followed by a synthesized visualization that can guide further research and development in this area. Our study will assist users in selecting the most suitable Kubernetes visualization tool and encourage researchers and the community to explore new approaches in Kubernetes visualization.
We consider a scenario that utilizes road side units (RSUs) as distributed caches in connected vehicular networks. The goal of the use of caches in our scenario is for rapidly providing contents to connected vehicles ...
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ISBN:
(数字)9781665471770
ISBN:
(纸本)9781665471770
We consider a scenario that utilizes road side units (RSUs) as distributed caches in connected vehicular networks. The goal of the use of caches in our scenario is for rapidly providing contents to connected vehicles under various traffic conditions. During this operation, due to the rapidly changed road environment and user mobility, the concept of age-of-information (AoI) is considered for (1) updating the cached information as well as (2) maintaining the freshness of cached information. The frequent updates of cached information maintain the freshness of the information at the expense of network resources. Here, the frequent updates increase the number of data transmissions between RSUs and MBS;and thus, it increases system costs, consequently. Therefore, the tradeoff exists between the AoI of cached information and the system costs. Based on this observation, the proposed algorithm in this paper aims at the system cost reduction which is fundamentally required for content delivery while minimizing the content AoI, based on Markov Decision Process (MDP) and Lyapunov optimization.
Surrogate-assisted evolutionary algorithms (SAEAs) have become a popular method to solve data-driven optimization problems (DOPs), which are common in industry. However, with the development of the Internet of Things,...
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This paper presents a secure and flexible process integration approach enabling distributed data fusion in military IoT applications. It seamlessly combines two recently developed technologies, the Dynamic Process Int...
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