Exploratory study to explore the role of ICT in the process of knowledge management in an Indian business environment

In the 21st century and the emergence of a digital economy, knowledge and the knowledge base economy are rapidly growing. To effectively be able to understand the processes involved in the creating, managing and sharing of knowledge management in the business environment is critical to the success of an organization. This study builds on the previous research of the authors on the enablers of knowledge management by identifying the relationship between the enablers of knowledge management and the role played by information communication technologies (ICT) and ICT infrastructure in a business setting. This paper provides the findings of a survey collected from the four major Indian cities (Chennai, Coimbatore, Madurai and Villupuram) regarding their views and opinions about the enablers of knowledge management in business setting. A total of 80 organizations participated in the study with 100 participants in each city. The results show that ICT and ICT infrastructure can play a critical role in the creating, managing and sharing of knowledge in an Indian business environment

A quick-response real-time stepping stone detection scheme

Stepping stone attacks are often used by network intruders to hide their identities. To detect and block stepping stone attacks, a stepping stone detection scheme should be able to correctly identify a stepping-stone in a very short time and in real-time. However, the majority of past research has failed to indicate how long or how many packets it takes for the monitor to detect a stepping stone. In this paper, we propose a novel quick-response real-time stepping stones detection scheme which is based on packet delay properties. Our experiments show that it can identify a stepping stone within 20 seconds which includes false positives and false negatives of less than 3%

Efficient k-means++ approximation with MapReduce

PublishedJournal Articlek-means is undoubtedly one of the most popular clustering algorithms owing to its simplicity and efficiency. However, this algorithm is highly sensitive to the chosen initial centers and thus a proper initialization is crucial for obtaining an ideal solution. To address this problem, k-means++ is proposed to sequentially choose the centers so as to achieve a solution that is provably close to the optimal one. However, due to its weak scalability, k-means++ becomes inefficient as the size of data increases. To improve its scalability and efficiency, this paper presents MapReduce k-means++ method which can drastically reduce the number of MapReduce jobs by using only one MapReduce job to obtain k centers. The k-means++ initialization algorithm is executed in the Mapper phase and the weighted k-means++ initialization algorithm is run in the Reducer phase. As this new MapReduce k-means++ method replaces the iterations among multiple machines with a single machine, it can reduce the communication and I/O costs significantly. We also prove that the proposed MapReduce k-means++ method obtains O(α2) approximation to the optimal solution of k-means. To reduce the expensive distance computation of the proposed method, we further propose a pruning strategy that can greatly avoid a large number of redundant distance computations. Extensive experiments on real and synthetic data are conducted and the performance results indicate that the proposed MapReduce k-means++ method is much more efficient and can achieve a good approximation.This work was supported by the National Science Foundation for Distinguished Young Scholars of China under Grant No. of 61225010, National Nature Science Foundation of China (Nos. 61173162, 61173165, 61370199, 61300187, 61300189, and 61370198), New Century Excellent Talents (No. NCET-10-0095), the Fundamental Research Funds for the Central Universities (Nos. 2013QN044 and 2012TD008)

Autonomic Cloud Computing: Open Challenges and Architectural Elements

As Clouds are complex, large-scale, and heterogeneous distributed systems, management of their resources is a challenging task. They need automated and integrated intelligent strategies for provisioning of resources to offer services that are secure, reliable, and cost-efficient. Hence, effective management of services becomes fundamental in software platforms that constitute the fabric of computing Clouds. In this direction, this paper identifies open issues in autonomic resource provisioning and presents innovative management techniques for supporting SaaS applications hosted on Clouds. We present a conceptual architecture and early results evidencing the benefits of autonomic management of Clouds.Comment: 8 pages, 6 figures, conference keynote pape

Efficient unknown tag identification protocols in large-scale RFID systems

PublishedJournal ArticleOwing to its attractive features such as fast identification and relatively long interrogating range over the classical barcode systems, radio-frequency identification (RFID) technology possesses a promising prospect in many practical applications such as inventory control and supply chain management. However, unknown tags appear in RFID systems when the tagged objects are misplaced or unregistered tagged objects are moved in, which often causes huge economic losses. This paper addresses an important and challenging problem of unknown tag identification in large-scale RFID systems. The existing protocols leverage the Aloha-like schemes to distinguish the unknown tags from known tags at the slot level, which are of low time-efficiency, and thus can hardly satisfy the delay-sensitive applications. To fill in this gap, two filtering-based protocols (at the bit level) are proposed in this paper to address the problem of unknown tag identification efficiently. Theoretical analysis of the protocol parameters is performed to minimize the execution time of the proposed protocols. Extensive simulation experiments are conducted to evaluate the performance of the protocols. The results demonstrate that the proposed protocols significantly outperform the currently most promising protocols.This work was supported by NSFC (Grant Nos. 60973117, 61173160, 61173162, and 60903154), New Century Excellent Talents in University (NCET) of Ministry of Education of China, The Research Fund for the Doctoral Program of Higher Education (Program No. 20130041110019) and the National Science Foundation for Distinguished Young Scholars of China (Grant No. 61225010)

Efficient resource Utilization in Cloud Computing Using Revised ROSP Algorithm (ERROSP)

Computing world these days is occupied by the Seventh Heaven. The most important question, it is necessary in this visualization is it to play an important role in the enterprise. Through this rapid development in the enterprise the most varieties of personal desire to save a lot of cash, time, hours and properties, which may increase in the area of electronic commerce. The cloud computing world is spreading rapidly on the Internet. Therefore, the basic definition of analysing cloud computing from around the world, often too, because it tells the calculation under application of services to assist the network and access to hardware and software running on the system may give the service. "A standardized IT capability (services, software or infrastructure) technology pay-per-use, self-service manner provided by the Internet." In the cloud of the most important research is Buckley RAD defines cloud computing as. The service itself has long been known as software as a service (SaaS). Data center hardware and software is what we call clouds. When the cloud is made available to the public in the way of a pay-as-you-go, which we call the public cloud; business being sold is utility computing. We use the term private cloud is an enterprise or other organization, not available to the general public within the data center. Therefore, SaaS, and cloud computing is the sum of utility computing, but not including private clouds. People can users or SaaS provider, or user or utility computing vendor. "Analysis goal of this paper is to find the user's needs, the best cloud service provider and cloud metaphysics programming algorithm is mainly based programming techniques. Actually speaking, cloud computing, programming side measure died in a cloud computing environment to take advantage of cloud computing provides a convenient broker execution management system to bring good prescription measurement programming techniques

Multi-Agent System Approach for Trustworthy Cloud Service Discovery

Accessing the advantages of cloud computing requires that a prospective user has proper access to trustworthy cloud services. It is a strenuous and laborious task to find resources and services in a heterogeneous network such as cloud environment. The cloud computing paradigm being a form of distributed system with a complex collection of computing resources from different domains with different regulatory policies but having a lot of values could enhance the mode of computing. However, a monolithic approach to cloud service discovery cannot help the necessities of cloud environment efficiently. This study put forward a distributive approach for finding sincere cloud services with the use of Multi-Agents System for ensuring intelligent cloud service discovery from trusted providers. Experiments were carried out in the study using CloudAnalyst and the results indicated that extending the frontiers MAS approach into cloud service discovery by way of integrating trust into the process improves the quality of service in respect of response time and scalability. A further comparative analysis of the Multi-Agents System approach for cloud service discovery to monolithic approach showed that Multi-Agents System approach is highly efficient, and highly flexible for trustworthy cloud service discovery

Fault-tolerant scheduling with dynamic number of replicas in heterogeneous systems

In the existing studies on fault-tolerant scheduling, the active replication schema makes use of&nbsp;&epsilon; + 1 replicas for each task to tolerate&nbsp;&epsilon; failures. However, in this paper, we show that it does not always lead to a higher reliability with more replicas. Besides, the more replicas implies more resource consumption and higher economic cost. To address this problem, with the target to satisfy the user&rsquo;s reliability requirement with minimum resources, this paper proposes a new fault tolerant scheduling algorithm: MaxRe. In the algorithm, we incorporate the reliability analysis into the active replication schema and the theoretical analysis and experiments prove that the MaxRe algorithm&rsquo;s schedule can certainly satisfy user&rsquo;s reliability requirements. And the MaxRe scheduling algorithm can achieve the corresponding reliability with at most 70% fewer resources than the FTSA algorithm.</p