This paper discourses the typical ways to access system of the battery energy storage system. To realize the battery energy storage system based on IEC 61850, hierarchical information architec- ture for battery energy storage system is presented, the general design and implementation me- thods for device information model are elaborated, and the communication methods of the archi- tecture are proposed. Example of battery energy storage system information model based on IEC 61850 tests that the battery energy storage system information architecture established is feasi- ble.
To demonstrate the capabilities of the methodology, we have conducted an extensive analysis of the design of a real, commercial cache RAID storage system. To our knowledge, this kind of analysis of a cache-based RAID system has not been accomplished either in academia or in the industry. The dependability measures used to charac- terize the system include coverage of the different error de- tection mechanisms employed in the system, error latency distribution classified according to the origin of an error, error accumulation in the cache memory and disks, and frequency of data reconstruction in the cache memory. To analyze the system under realistic operational conditions, we used real input traces to drive the simulations. It is im- portant to emphasize that an analytical modeling of the system is not appropriate in this context due to the com- plexity of the architecture, the overlapping of error detec- tion and recovery mechanisms, and the necessity of captur- ing the latent errors in the cache and the disks. Hierarchical simulation offers an efficient method to accomplish the above task and allows detailed analysis of the system to be performed using real input traces.
The strategy makes grading the different OSD in terms of OSD ability possible. Hierarchical model is shown in Figure.4. In this scenario, MDS sends objects to a local queue of OSD with FCFS rule. Logic OSD is logically divided into two levels, distribution layer and the polling layer.
of Internet-based information systems. Various models have been proposed to categorize and rank system interoperability qualitatively. LISA (Levels of Information Systems Interoperability), proposed by C4ISR architecture working group, is one of the widely used reference framework for defining, evaluating, and measuring system interoperability . It uses four properties to evaluate interoperability including: the Process (P), such as technical standards, architecture, policy, and regulations; the Application (A), such as the software for information exchanging, processing, and management; the Infrastructure (I), such as system services, communication protocols, remote procedure calls; and the Data (D), such as the storage, format, and semantic of application data. For each property, it defines five levels ranking from low to high as isolated, connected, functional, domain, and enterprise. NC3TA (NATO C3 Technical Architecture Reference Model for Interoperability)  defines a group of standards, architecture and reference models. It focuses on the evaluation of system capability of automatic exchange and interpretation of well-defined structural data. Tolk  pointed out the importance of conceptual interoperability model and proposes LCIM (levels of Conceptual Interoperability Model). LCIM defines 7 levels of interoperability from level 0 to level 6 including no interoperability, technical interoperability, syntactic interoperability, semantic interoperability, pragmatic interoperation, dynamic interoperability, and conceptual interoperability. The highest level, conceptual interoperability, requires “fully specified, but implementation independent model”.
of learning objects and their components using learning patterns. On the other hand, in [7; 8], the authors proposes the use of design patterns for creating adaptable learning objects. In  the adaptivity is based on the use of competence description ontology and learner‟s competence records. Other authors, like [4; 2; 20; 19] referred that the adaptivity of the learning object is accomplished by situating the learning style and preferences to the user. The learning object should consider user needs to present mediatic objects according to their learning style (auditory, pictures, text, tactile kinesthetic and internal kinesthetic.
Above Figure 2 shows our four tier Mobile agent based hierarchal architecture for Wireless Sensor Network. There are four levels in this model. At the highest (First) level, Base station receives data from clouds and sends it to users as per their requirement. At second level, there are various clouds communicate with co-ordinator heads to receive data and transmit it to BS. Clouds provide the facility to co-ordinator heads to store large amount of data. At third level, CHs will collect sensed data from various sensor nodes and store it in the clouds. Data stored in cloud is analyzed and refined by cloud for future use. At fourth level or lowest level, we find the sensor nodes which are responsible for monitoring the surrounding environment, collecting sensed data and then the transfer of their data to the next level which is the co-ordinator heads.
of data, including temperature and movement updates, etc. By increasing the total sensor numbers, the amount of collected data in the long run are extremely enormous. Most sensors use battery for their energy production. Thus they have a significant limitation in energy. In other words, this resource is critical. In brief, a huge amount of sensor data along with the limitation of most sensors in computational power and especially lack of efficient, long-last and reliable energy suppliers, all these together necessitate the sensors to use battery as their energy supplier. Hence a minor improvement can cause a significant promotion in the life time, which is the time that elapses from network inception to death of the whole network. But the battery industry has faced difficulties in achieving this. So we suggest more efficient software approaches like more efficient algorithms in order to reduce energy consumption of the overall network. Our proposed method is concerning how we should store data so that we can respond to semantic queries effectively and efficiently in terms of energy consumption. For example, requisites are disseminated in semantic web based queires on behalf of users, which may be closer to human language, following with less energy consumption of the network. NSSSD is the combination of a hierarchical method with the help of LEACH where sensor nodes are arranged into some clusters with semantic web technolog. Hierarchical method we are using resembles tree structures with 3 levels. Sink node is the root of the hierarchy, cluster heads are children of the sink node. All other sensor nodes are located as leafs of the tree. After arranging sensors we need to schedule data transmissions in order to make sure the safety of the data transmission process is maintained. The proposed method consists
OpenStack believes in open source, open design, open development, all in an open community that encourages participation by anyone. The long- term vision for OpenStack is to produce a ubiquitous open source cloud computing platform that meets the needs of public and private cloud providers regardless of size. OpenStack services control large pools of com- pute, storage, and networking resources throughout a data center. The technology behind OpenStack consists of a series of interrelated projects delivering various components for a cloud infrastructure solu- tion. Each service provides an open API so that all of these resources can be managed through a dashboard that gives administrators control while empowering users to provision resources through a web interface, a com- mand-line client, or software development kits that support the API. Many OpenStack APIs are extensible, meaning you can keep compatibility with a core set of calls while providing access to more resources and innovating through API extensions. The OpenStack project is a global collaboration of developers and cloud computing technologists. The project produces an open standard cloud computing platform for both public and private clouds. By focusing on ease of implementation, massive scalability, a vari- ety of rich features, and tremendous extensibility, the project aims to deliv- er a practical and reliable cloud solution for all types of organizations.
Hierarchical Mobile IPv6 management (HMIPv6)  divides mobile node’s (MN) mobility  into micro-mobility and macro-mobility. When a MN moves within a particularly hierarchical domain, then micro-mobility; In this case, HMIPv6 utilize local mobility management to reduce the amount of signaling generated by the registration to the correspondent nodes (CNs) and to the home agent (HA).when the MN moves out to a new domain, then macro-mobility, the mobility of the MN will be managed by the standard Mobile IPv6 management (MIPv6) . Mobile Anchor Point (MAP) is a substitute of “Home Agent” (HA) in each domain of the network which hides user’s mobility from the outer domain. Then the binding updates are sent from MN directly to MAP rather than more distant HA or CNs when the MN stays in a specific region; meaning that MN’s exact position is hidden from outer region and the signaling overhead is reduced. The MN needs to register
This paper is about Hadoop ecosystem and has explored its major components as well as Hadoop setup. Various aspects of data storage is focused like HDFS and its architecture. The process of installation of Hadoop setup is analyzed. HDFS ensures data integrity throughout the cluster considering features like maintaining transaction logs. Another feature is validating checksum-an effective error detection technique wherein numerical value is assigned to a transmitted message on the basis of number of bits. HDFS maintains replicated copies of data blocks to avoid corruption of file due to failure of server. This paper also deals with MapReduce framework, which is an integration of different functions to sort,process and analyze bigdata.
Abstract—Cloud storage is the lower layer of the cloud computing system that supports other layers above it. Up to now the likes of Google, Microsoft, IBM, and Amazon have been providing cloud storage services. Since its effi- cient way to store and manage important data, the offer of free storage attracts researchers. As a result, cloud storage research will not only track trends, but will also have high application value. Therefore, this paper, introduces a novel model of data storage and backup in cloud storage, that optimally combines customer storage resources with service providers, so that redundancy, storage strategy and configuration properties can be adjusted adequately to the needs of the storage service consumer. In this paper, we review two of the backup tech- nologies (Snapshot and D2D), that are used in this model. In addition, the first contribution is bound to both determining consumer requirements and choosing the provider. Next—life cycle and phases of preparation model for data storage services. Furthermore, we present place and form of the model in cloud storagearchitecture. The model aims to increase the availability of data and reduces the loss of data in storage environments.
Tenant performance isolation is a key controller ap- plication in this paper that illustrates the benefits of the architecture. The isolation problem itself has been ex- tensively studied and there are many customized solu- tions in the context of several resources: for example, for disks [9, 28], for multi-tenant network control [2, 3, 20], for multi-tenant storage control [8, 25], for latency con- trol in networks  and for multi-resource centralized systems . Distributed rate limiting has also been stud- ied in the past . In contrast to these proposals, IOFlow offers a single framework for a wide range of performance isolation policies. The presence of a con- troller with global visibility and the programmable data- plane stages allowed us to write simple centralized algo- rithms to achieve the policies. As such, we believe that other algorithms, such as recent ones by Shue et al.  would equally benefit from our system’s support.
Cybercrime is a criminal activity that utilizes computers and the internet as a media in committing its crimes. In solving the case of cybercrime, it is useful with the help of digital forensics. The critical component in digital forensics is electronic evidence that has a physical form and digital evidence that has form in the binary file. Both types of evidence require handling in the storage process with different treatments. In this case, physical evidence of physical nature will be stored in the evidence room while digital evidence will be stored in evidence storage. The solution that has existed so far is through the mechanism of storing digital evidence stored in evidence storage based on internal storage with limited accessibility to one device. It causes inflexibility and effectiveness to support collaborative efforts between officers and law enforcement in the process of investigating and handling digital evidence. This research is to develop previous research on digital evidence storage and handling systems. This paper presents a solution for centralized and network- based digital evidence storagearchitecture to address the weaknesses of previously available solutions. Flexibility repositories based on SAN (Storage Area Network) and web- based technology are used as network-based centralized storage architectures. The system is expected to help between law enforcement in terms of chain of custody management for digital evidence.
applied to categorise both fluvial and aeolian sedimentary successions (e.g., Brookfield, 1977; Allen, 1983; Miall, 1985). Although only some authors of deep-marine hierarchical schemes might have directly acknowledged these influences (e.g., Ghosh & Lowe, 1993, Pickering et al., 1995, Gardner & Borer, 2000, Gardner et al., 2003, Terlaky et al., 2016 and Pickering & Cantalejo, 2015; see Table 1 and Fig. 1), all the reviewed schemes implicitly recognise architectural hierarchy using the principles of architectural-element analysis to some degree. Such commonalities suggest that reconciliation between hierarchies should be possible (see also Section 3.5, below). Nevertheless, difficulties remain in trying to make definitive links between the hierarchical orders of different schemes. This is due in part to the differing significance given to particular types of diagnostic characteristic. For example, the hierarchy of Prélat et al. (2009) specifically focuses upon facies characteristics, while that of Deptuck et al. (2008) largely relies on stacking patterns of 3D architectural geometries. In addition, difficulties in observing key characters, as a result of the intrinsic complexity of
The Bachelor of Design (Product Design) is the first step towards becoming an industrial designer. To be a professional industrial designer, students are required to complete a three-year undergraduate degree and a Master of Design. Industrial designers create the form and function of the thousands of products people use every day. These include: electronic devices, appliances for the home, more efficient workplace products, tools for safer and more effective industrial applications, sports equipment to improve safety and performance, fashion accessories, new car concepts, toy and game designs, furniture and medical equipment. The degree has a strong emphasis on hands-on, practical experience through design studios, model making and prototyping and the opportunity for international study. Career opportunities
The increased integration of PMUs introduces new vulnerabilities to cyber-attacks, which if exploited by attackers, may have damaging consequences ranging from local power outage to complete blackout. Recently, multiple PMU vulnerabilities have been reported by Arbiter ; these vulnerabilities can cause a Denial of Service (DoS) as identified in the Arbiter Systems Power Sentinel PMU. Moreover, some PMU vendors such as the National Instruments PMU (NI Grid Automation System) provide Linux-based PMUs that can be subject to linux worm/malware attacks (such as Moose and Darlloz.A). Many research efforts toward building a secure and reliable distributed WAMS architecture have been proposed recently.
The first-generation algorithm for HTM was called Zeta which was designed and published in the year 2007 by Dileep George. The work presented that HTM Zeta was an unsupervised algorithm and utilized the Bayesian inference and Markov graphs for pattern recognition. The algorithm accepted time varying data as its input and followed offline learning process. The algorithm consisted of Zeta nodes which are considered as the fundamental working units of the network for Zeta. The nodes are hierarchically placed in the shape of a tree. Multiple nodes in the tree constituted a region. The nodes at the lower level receive the data from the input and pass the information on to the higher-level nodes that are connected to it. The information obtained from the bottom nodes are converged to obtain the representation of the data objects. The nodes were responsible for learning the patterns and the learned pattern representations storage. The complete discussion of the working principles of the algorithm is found in .
of trust stipulated by explicit rules and roles. An efficient access control system records and timestamps all communications and transactions so that access to enterprise network and information system can be audited later. In an enterprise application, group members subscribe to different resource streams, or possibly multiples of them. Thus, it is necessary to develop group access control mechanism that supports the multi-level access privileges, referred to as the hierarchical access control ([SR04]).