Distributed Computing Environment Research Articles

Adaptive Workload Scheduling Design in Parallel Computational Framework

In the recent years, many researchers have showed a great deal of interest to improve the scheduling of workload in the cloud platforms. On the other hand, to carry out the execution of the scientific workloads in the cloud environment, it consumes much time and is expensive; hence, it is neither time efficient nor cost-efficient. Due to this reason, many research studies have been carried, by which the researchers tend to reduce the processing time and make a cost-efficient method as the users are charged based on the usage. Very few studies have been done to optimize the cost with processing time and energy parameters together in order to meet the Service Level Agreement (SLA) and Quality of Service (QoS) of the workload task. Hence, in this paper, we present an Adaptive Workload Scheduling (AWS) model that ensures the Task Level SLA prerequisites in a heterogeneous distributed-computing environment. This AWS- model approach reduces the amount of energy and time needed to execute a given workloads. Cybershake scientific workload has been utilized for the studying proposed AWS model. When model was compared with the standard workload scheduling approach, our model reduced the consumption of cost, energy and time.

An Efficient Technique for Secure Message Broadcasting

In contemporary cryptographic discourse, traditional broadcast encryption (BE) schemes have emerged as a robust method for secure broadcasting to specific subsets of members within a group. However, these schemes typically necessitate the involvement of a trusted entity for the distribution of decryption keys, which introduces vulnerabilities. Conversely, group key agreement (GKA) protocols offer a means of negotiating a shared encryption key among a group of members across open networks, thereby ensuring that only authorized group members possess the capability to decrypt ciphertexts encrypted under this key. Nonetheless, GKA protocols lack the flexibility to allow senders to selectively exclude specific members from decrypting ciphertexts. In response to this dichotomy, we present a pioneering hybrid cryptographic primitive termed Contributory Broadcast Encryption (ConBE), which ingeniously amalgamates the strengths of both BE and GKA paradigms. In this innovative approach, a cohesive group of members collaboratively negotiates a shared public encryption key, with each member possessing an associated decryption key. This setup empowers senders, upon accessing the public group encryption key, to exercise granular control over decryption, selectively restricting access to a subset of designated recipients. Expounding upon this foundational framework, we introduce a ConBE scheme distinguished by succinct ciphertexts, thus optimizing computational efficiency without compromising on security guarantees. Through rigorous analysis, our scheme is proven to be fully collusion-resistant under the decision n- Bilinear Diffie-Hellman Exponentiation (BDHE) assumption, thereby ensuring robust security within the standard cryptographic model. Furthermore, in a complementary contribution, we unveil a novel BE scheme endowed with aggregatable properties, which hold paramount significance in the construction of advanced cryptographic protocols. These properties facilitate the aggregation of decryption rights across multiple ciphertexts, thereby enhancing scalability and versatility in cryptographic applications. Our comprehensive exploration and formalization of ConBE, alongside the development of efficient cryptographic schemes, represent a significant stride forward in the realm of secure data transmission and access control mechanisms. This endeavor underscores our commitment to advancing cryptographic methodologies that reconcile security, efficiency, and flexibility in contemporary distributed computing environments

Scalable Communication-Induced Checkpointing Protocol with Little Overhead for Distributed Computing Environments

The existing communication-induced checkpointing protocols may not scale well due to their slow acquisition of the most recent timestamps of the next checkpoints of other processes. Accurate situation awareness with diversified information conveyance paths is needed to reduce the number of unnecessary forced checkpoints taken as few as possible. In this paper, a scalable communication-induced checkpointing protocol is proposed to considerably cut down the possibility of performing unnecessary forced checkpointing by exploiting the beneficial features of reliable communication channels. The protocol enables the sender of an application message to swiftly attain the most recent timestamp-related information of the next checkpoint of its receiver and accelerate the spread of the information to others, with little overhead. This behavioral feature may significantly elevate the accuracy of the awareness of the situations in which forced checkpointing is actually needed for useless checkpoint-free recovery. In addition, it generates no extra control message and no message logging overhead while significantly lessening the latency of message sending. Moreover, the protocol can always be operated under the non-deterministic execution model. The evaluation results indicate that the proposed protocol outperforms the existing ones at the reduced forced checkpointing overheads from 12.5% to 84.2%, and at the reduced total execution times from 2.5% to 11.5%.

An Extensible Approach to Searching and Selecting Data Sources for Materialized Big Data Integration in Distributed Computing Environments

An Extensible Approach to Searching and Selecting Data Sources for Materialized Big Data Integration in Distributed Computing Environments

Dynamic Context Awareness of Universal Middleware based for IoT SNMP Service Platform

This study focused on the Universal Middleware design for the IoT (Internet of Things) service gateway for the implementation module of the convergence platform. Recently, IoT service gateway including convergence platform could be supported on dynamic module system that is required mounting and recognized intelligent status with the remote network protocol. These awareness concepts support the dynamic environment of the cross-platform distributed computing technology is supported by these idea as a Universal Middleware for network substitution. Distribution system commonly used in recent embedded systems include CORBA (Common Object Request Broker Architecture), RMI (Remote Method Invocation), DCE (Distributed Computing Environment) for dynamic service interface, and suggested implementations of a device object context. However, the aforementioned technologies do not support each standardization of application services, communication protocols, and data, but are also limited in supporting inter-system scalability. In particular, in order to configure an IoT service module, the system can be simplified, and an independent service module can be configured as long as it can support the standardization of modules based on hardware and software components. This paper proposed a design method for Universal Middleware that, by providing IoT modules and service gateways with scalability for configuring operating system configuration, may be utilized as an alternative. This design could be a standardized interface provisioning way for hardware and software components as convergence services, and providing a framework for system construction. Universal Middleware Framework could be presented and dynamic environment standardization module of network protocols, various application service modules such as JINI (Apache River), UPnP (Universal Plug & Play), SLP (Service Location Protocol) bundles that provide communication facilities, and persistence data module. In this IoT gateway, management for based Universal Middleware framework support and available for each management operation, application service component could be cross-executed over SNMP (Simple Network Management Protocol) version 1, version 2, and version 3. The way of SNMP extension service modules are conducted cross-support each module and independent system meta-information that could be built life cycle management component through the MIB (Management Information Base) information unit analysis. Therefore, the MIB role of relation with the Dispatcher applied to support multiple concurrent SNMP messages by receiving incoming messages and managing the transfer of PDU (Protocol Data Unit) between the RFC 1906 network in this study. Results of the study revealed utilizing Universal Middleware that dynamic situations of context objects with mechanisms and tools to publish information could be consisted of IoT to standardize module interfaces to external service clients as a convergence between hardware and software platforms.

A Two-stage Multi-population Genetic Algorithm with Heuristics for Workflow Scheduling in Heterogeneous Distributed Computing Environments

Workflow scheduling in Heterogeneous Distributed Computing Environments (HDCEs) is a NP-hard problem. Although a number of scheduling approaches have been proposed for workflow scheduling in HDCEs, there is still a room and need for improvement. To fill the gaps, this study formulates workflow scheduling problem in HDCEs as a complete, solvable and extensible integer programming mathematical model with precedence and resource constraints that provides a theoretical foundation for developing workflow scheduling strategy. Then, this study develops a novel two-stage multi-population genetic algorithm with heuristics for workflow scheduling. In particular, two-stage multi-population coevolution strategy is employed with designed novel methods for population initialization, genetic operation, individual decoding and improvement. To estimate the validity, extensive experiments are designed and conducted on various scenarios based on real and random workflow applications. The results have shown the practical viability of the proposed algorithm outperforming conventional approaches.

Method and Algorithms for Adaptive Multiagent Resource Scheduling in Heterogeneous Distributed Computing Environments

Method and Algorithms for Adaptive Multiagent Resource Scheduling in Heterogeneous Distributed Computing Environments

Efficiently Supporting Online Privacy-Preserving Data Publishing in a Distributed Computing Environment

There has recently been an increasing need for the collection and sharing of microdata containing information regarding an individual entity. Because microdata typically contain sensitive information on an individual, releasing it directly for public use may violate existing privacy requirements. Thus, extensive studies have been conducted on privacy-preserving data publishing (PPDP), which ensures that any microdata released satisfy the privacy policy requirements. Most existing privacy-preserving data publishing algorithms consider a scenario in which a data publisher, receiving a request for the release of data containing personal information, anonymizes the data prior to publishing—a process that is usually conducted offline. However, with the increasing demand for the sharing of data among various parties, it is more desirable to integrate the data anonymization functionality into existing systems that are capable of supporting online query processing. Thus, we developed a novel scheme that is able to efficiently anonymize the query results on the fly, and thus support efficient online privacy-preserving data publishing. In particular, given a user’s query, the proposed approach effectively estimates the generalization level of each quasi-identifier attribute, thereby achieving the k-anonymity property in the query result datasets based on the statistical information without applying k-anonymity on all actual datasets, which is a costly procedure. The experiment results show that, through the proposed method, significant gains in processing time can be achieved.

Communication Pattern Models: An Extension of Action Models for Dynamic-Network Distributed Systems

Halpern and Moses were the first to recognize, in 1984, the importance of a formal treatment of knowledge in distributed computing. Many works in distributed computing, however, still employ informal notions of knowledge. Hence, it is critical to further study such formalizations. Action models, a significant approach to modeling dynamic epistemic logic, have only recently been applied to distributed computing, for instance, by Goubault, Ledent, and Rajsbaum. Using action models for analyzing distributed-computing environments, as proposed by these authors, has drawbacks, however. In particular, a direct use of action models may cause such models to grow exponentially as the computation of the distributed system evolves. Hence, our motivation is finding compact action models for distributed systems. We introduce communication pattern models as an extension of both ordinary action models and their update operator. We give a systematic construction of communication pattern models for a large variety of distributed-computing models called dynamic-network models. For a proper subclass of dynamic-network models called oblivious, the communication pattern model remains the same throughout the computation.

Models of the Computer Intellectualization Optimal Strategy of the Power Supply Fast-Flowing Technological Processes of the Railways Traction Substations

Based on analysis of the problem of the power supply networks of railways innovative transformation, the direction of research is substantiated related to organization of the optimal strategy of computerized intellectualization of the power supply processes to the railways traction substations. The logical structure of a distributed computer environment developed in the form of graph, which adequately reflects the topology of the organization of the power supply system. A differential mathematical model of the computer architecture of the power supply control is proposed. An intelligent method for finding the optimal strategy for the intellectualization of the power supply processes was proposed to guarantee the specified indicators of the optimal functioning of individual nodes and segments of the power supply management computer network.

Design and Application of Distributed Computing Environment Based on Data Drive

This paper proposes a distributed computing environment based on data-driven mechanism, which can be deployed on different levels of Industrial Internet, designs and implements an Industrial Internet architecture with high reusability and rapid deployment. This architecture has the consistency of the computing environment in the cloud and terminal control layer, which is beneficial to the realization of remote management and collaborative control of Industrial Internet. Data driven technology enables heterogeneous industrial equipment to achieve interconnection and interworking at a low cost. The multi-engine computing environment constructed by it is not only an effective method to solve the application design and development of complex systems, but also a key technology to realize edge computing and fog computing. This paper designed a corresponding test bed platform, test results show that the technology can not only provide connectivity of heterogeneous data source and efficient technical support, and to ensure that the distributed industrial equipment real-time and synchronization of data transmission, but also has the strong edge computing capabilities to cope with the constantly generated data stream, and reducing the pressure of the cloud server storage, computing.

Programmable Chip Based High Performance MEC Router for Ultra-Low Latency and High Bandwidth Services in Distributed Computing Environment

Programmable Chip Based High Performance MEC Router for Ultra-Low Latency and High Bandwidth Services in Distributed Computing Environment

Parallel graph algorithms in constant adaptive rounds

We study fundamental graph problems such as graph connectivity, minimum spanning forest (MSF), and approximate maximum (weight) matching in a distributed setting. In particular, we focus on the Adaptive Massively Parallel Computation (AMPC) model, which is a theoretical model that captures MapReduce-like computation augmented with a distributed hash table. We show the first AMPC algorithms for all of the studied problems that run in a constant number of rounds and use only O ( n ϵ ) space per machine, where 0 < ϵ < 1. Our results improve both upon the previous results in the AMPC model, as well as the best-known results in the MPC model, which is the theoretical model underpinning many popular distributed computation frameworks, such as MapReduce, Hadoop, Beam, Pregel and Giraph. Finally, we provide an empirical comparison of the algorithms in the MPC and AMPC models in a fault-tolerant distributed computation environment. We empirically evaluate our algorithms on a set of large real-world graphs and show that our AMPC algorithms can achieve improvements in both running time and round-complexity over optimized MPC baselines.

Tree-Like Distributed Computation Environment with Shapp Library

Despite the rapidly growing computing power of computers, it is often insufficient to perform mass calculations in a short time, for example, simulation of systems for various sets of parameters, the searching of huge state spaces, optimization using ant or genetic algorithms, machine learning, etc. One can solve the problem of a lack of computing power through workload management systems used in local networks in order to use the free computing power of servers and workstations. This article proposes raising such a system to a higher level of abstraction: The use in the .NET environment of a new Shapp library that allows remote task execution using fork-like operations from Portable Operating System Interface for UNIX (POSIX) systems. The library distributes the task code, sending static data on which task force is working, and individualizing tasks. In addition, a convenient way of communicating distributed tasks running hierarchically in the Shapp library was proposed to better manage the execution of these tasks. Many different task group architectures are possible; we focus on tree-like calculations that are suitable for many problems where the range of possible parallelism increases as the calculations progress.

Toward Distributed Computing Environments with Serverless Solutions in Edge Systems

Computation offloading through stateless applications is gaining momentum thanks to the emergence of serverless frameworks with inherent scalability properties. However, adoption of a serverless framework in an edge computing system requires careful consideration to keep its advantages unscathed. In the cloud, micro-services are scaled automatically according to demands, but in edge computing this would incur a significantly higher cost than in a data center and cannot be as fluid. This is especially relevant in scenarios where edge nodes are spread across large areas and have relatively small computation capabilities. In this article we propose to overcome this issue by adapting the allocation of demands to the currently allocated micro-services at short timescales, with two alternative mechanisms designed for different target scenarios, both aimed at enabling distributed computing environments. The proposed solution can be integrated within the ETSI MEC standard, which specifies a reference architecture and open service interfaces. Our contribution is validated in a proof-of-concept scenario with a prototype implementation released as open source.

Limit Value Task Scheduling (LVTS): an Efficient Task Scheduling Algorithm for Distributed Computing Environment

The grid computational environment suits to meet the computational demands of large, diverse groups of tasks. Assigning tasks to heterogeneous wide spread resources seems complex and is termed as an NP-Complete problem. A new task scheduling algorithm, called Limit Value Task Scheduling Algorithm (LVTS) is presented to efficiently identify the appropriate resources, which is responsible for the scheduling process. The proposed algorithm (LVTS) schedules the tasks to the appropriate resources by calculating the limit value of the tasks and the ceil value of the tasks which represents the completion time of the last tasks scheduled in the resource with highest processing capacity. The efficiency of the (LVTS) measured based on makespan and resource utilization. Experimental results indicates LVTS algorithm sounds good than the Min-min on both makespan and resource utilization.

Gossip-based fault-tolerant load balancing algorithm with low communication overhead

In large-scale distributed-computing environments, numerous factors may affect the predictable performance of load balancing policies causing variable load distribution in the network and bottlenecks. This paper presents a two-level load balancing algorithm for solving the dynamic load balancing problem considering the loss of processors and connectivity of the network. The proposed method privileges local load balancing over global load balancing thus reduces the communication cost over the global network. To further minimize communication costs and to handle loss of connectivity, the algorithm proposes a new communication model for global communication among the processors. The performance, correctness, and scalability of the algorithm are analyzed which show that our algorithm requires O(log m) rounds and O(m log m) messages for m clusters and achieves minimum cluster and global load deviation. Simulation results also support our analytical studies.

Optimal Selection of Crowdsourcing Workers Balancing Their Utilities and Platform Profit

In a mobile crowdsourcing system (MCS), a platform outsources sensing tasks to numerous mobile worker devices. The collected data are analyzed and the processed information is shared among many other interested users. The platform pays the workers for the sensing data and earns money from the users receiving processed information services. Distributing the sensing workloads among the potential workers so as to maintain the required data quality and to make a reasonable amount of profit is a challenging problem for such a platform. In this paper, we develop a workload allocation policy that makes a reasonable tradeoff between worker utilities and platform profit. It quantifies the utility (i.e., the quality of sensed data) of a worker as a function of worker mobility, current location, and past sensing records. The workload allocation problem is formulated as a multiobjective nonlinear programming (MONLP) problem which aims to make the desired tradeoff between worker utilities and platform profit. The allocation problem is shown to be NP-hard and thus we develop two greedy algorithms with relaxed constraints to achieve polynomial time solutions. Performance of the proposed workload allocation policy is evaluated in a distributed computation environment using MATLAB. The results show its effectiveness compared to state-of-the-art methods in terms of platform profit, quality of sensing data, and request service satisfaction.

The Concept and Technologies of Quality of Geographic Information Service: Improving User Experience of GIServices in a Distributed Computing Environment

With the wide use of web technologies, service-oriented architecture (SOA), and cloud computing, more and more geographical information systems are served as GIServices. Under such circumstance, quality of geographic information services (QoGIS) has emerged as an important research topic of geoinformatics. However, it is not easy to understand the field since QoGIS has no formal standards, which is not only in regard to server-side performance and capabilities, but is also related with the quality of experience (QoE) during user interaction with GIServices. In this paper, we compare quality of service (QoS) and QoGIS research to understand the uniqueness of QoGIS. A conceptual framework is proposed to organize and interpret QoGIS research from the perspective of quality modeling, acquisition, and application, and we discuss the status, limitations, and future directions of this area. Overall, our analysis shows that new quality metrics will evolve from existing metrics to match the needs in concrete QoGIS applications, and user preferences need to be considered in quality modeling for GIServices. We discuss three approaches for the provision of QoGIS information and find that user feedback mining is an important supplementary source of quality information. Gaps between QoS and QoGIS research suggest that the GIService performance enhancement must not only consider the unique features of spatial data models and algorithms, but also system architecture, deployment, and user spatiotemporal access behaviors. Advanced service selection algorithms must be introduced to tackle the quality optimization problems of geoprocessing workflow planning. Moreover, a QoGIS-aware GIServices framework must be established to facilitate and ensure GISerivce discovery and interaction. We believe this bibliographic review provides a helpful guide for GIS researchers.

An Authentication Scheme for Distributed Computing Environment

In this era of information technology, the protection of personal sensitive information is one of the most challenging tasks which will not allow any human being to escape from browsing, sharing and holding information. In this scenario different service provider offers services for its users to share their personal sensitive information, resources and identity via distributed network. And attackers can easily pick this information from the open network due to lack of cross verification of the legality of peers. Almost no researcher claims with conviction about a foolproof secure authentication scheme for the said environment. In this regard, a robust authentication scheme is presented for the distributed computing environment which not only offers a secure cross verification of user validity but can also protect personal sensitive information and secure sharing of associated resources. The performance and security analysis at the end of this paper shows that the scheme is best among all available in the recent literature. All the narratives show that the scheme can easily be implemented in the recent era for the said purpose.