Abstract: Grid is an environment with millions of resources
which are dynamic and heterogeneous in nature. A computational
grid is one in which the resources are computing nodes and is meant
for applications that involves larger computations. A scheduling
algorithm is said to be efficient if and only if it performs better
resource allocation even in case of resource failure. Resource
allocation is a tedious issue since it has to consider several
requirements such as system load, processing cost and time, user’s
deadline and resource failure. This work attempts in designing a
resource allocation algorithm which is cost-effective and also targets
at load balancing, fault tolerance and user satisfaction by considering
the above requirements. The proposed Budget Constrained Load
Balancing Fault Tolerant algorithm with user satisfaction (BLBFT)
reduces the schedule makespan, schedule cost and task failure rate
and improves resource utilization. Evaluation of the proposed
BLBFT algorithm is done using Gridsim toolkit and the results are
compared with the algorithms which separately concentrates on all
these factors. The comparison results ensure that the proposed
algorithm works better than its counterparts.
Abstract: Recently, increasing the quality of experience (QoE) is
an important issue. Since performance degradation at cell edge
extremely reduces the QoE, several techniques are defined at
LTE/LTE-A standard to remove inter-cell interference (ICI). However,
the conventional techniques have disadvantage because there is a
trade-off between resource allocation and reliable communication.
The proposed scheme reduces the ICI more efficiently by using
channel state information (CSI) smartly. It is shown that the proposed
scheme can reduce the ICI with fewer resources.
Abstract: Femtocells are regarded as a milestone for next
generation cellular networks. As femtocells are deployed in an
unplanned manner, there is a chance of assigning same resource to
neighboring femtocells. This scenario may induce co-channel
interference and may seriously affect the service quality of
neighboring femtocells. In addition, the dominant transmit power of a
femtocell will induce co-tier interference to neighboring femtocells.
Thus to jointly handle co-tier and co-channel interference, we
propose an interference-free power and resource block allocation
(IFPRBA) algorithm for closely located, closed access femtocells.
Based on neighboring list, inter-femto-base station distance and
uplink noise power, the IFPRBA algorithm assigns non-interfering
power and resource to femtocells. The IFPRBA algorithm also
guarantees the quality of service to femtouser based on the
knowledge of resource requirement, connection type, and the
tolerable delay budget. Simulation result shows that the interference
power experienced in IFPRBA algorithm is below the tolerable
interference power and hence the overall service success ratio, PRB
efficiency and network throughput are maximum when compared to
conventional resource allocation framework for femtocell (RAFF)
algorithm.
Abstract: Mammography has been one of the most reliable
methods for early detection of breast cancer. There are different
lesions which are breast cancer characteristic such as
microcalcifications, masses, architectural distortions and bilateral
asymmetry. One of the major challenges of analysing digital
mammogram is how to extract efficient features from it for accurate
cancer classification. In this paper we proposed a hybrid feature
extraction method to detect and classify all four signs of breast
cancer. The proposed method is based on multiscale surrounding
region dependence method, Gabor filters, multi fractal analysis,
directional and morphological analysis. The extracted features are
input to self adaptive resource allocation network (SRAN) classifier
for classification. The validity of our approach is extensively
demonstrated using the two benchmark data sets Mammographic
Image Analysis Society (MIAS) and Digital Database for Screening
Mammograph (DDSM) and the results have been proved to be
progressive.
Abstract: The performance of any cooperative communication system depends largely on the selection of a proper partner. Another important factor to consider is an efficient allocation of resource like power by the source node to help it in forwarding information to the destination. In this paper, we look at the concepts of partner selection and resource (power) allocation for a distributed communication network. A type of non-cooperative game referred to as Trade-Off game is employed so as to jointly consider the utilities of the source and relay nodes, where in this case, the source is the node that requires help with forwarding of its information while the partner is the node that is willing to help in forwarding the source node’s information, but at a price. The approach enables the source node to maximize its utility by selecting a partner node based on (i) the proximity of the partner node to the source and destination nodes, and (ii) the price the partner node will charge for the help being rendered. Our proposed scheme helps the source locate and select the relay nodes at ‘better’ locations and purchase power optimally from them. It also aids the contending relay nodes maximize their own utilities as well by asking proper prices. Our game scheme is seen to converge to unique equilibrium.
Abstract: As creative economy is important theme for national policy, many countries have been raising investments through national R&D programs. Since not all of programs are aligned with the ultimate vision and R&D investment is one of the most decisive elements, the strategic fit of national R&D programs should be evaluated for effective resource allocation. This study aims at identifying the factors of strategic fit of national R&D program on the creative economy policy. For this purpose, the balanced scorecard (BSC) model for R&D is utilized to translate national strategic objectives into a set of coherent performance factors.
Abstract: Proper maintenance and preservation of significant cultural heritages or historic buildings is necessary. It can not only enhance environmental benefits and a sense of community, but also preserve a city's history and people’s memory. It allows the next generation to be able to get a glimpse of our past, and achieve the goal of sustainable preserved cultural assets. However, the management of maintenance work has not been appropriate for many designated heritages or historic buildings so far. The planning and implementation of the reuse has yet to have a breakthrough specification. It leads the heritages to a mere formality of being “reserved”, instead of the real meaning of “conservation”. For the restoration and preservation of cultural heritages study issues, it is very important due to the consideration of historical significance, symbolism, and economic benefits effects. However, the decision makers such as the officials from public sector they often encounter which heritage should be prioritized to be restored first under the available limited budgets. Only very few techniques are available today to determine the appropriately restoration priorities for the diverse historical heritages, perhaps because of a lack of systematized decision-making aids been proposed before. In the past, the discussions of management and maintenance towards cultural assets were limited to the selection of reuse alternatives instead of the allocation of resources. In view of this, this research will adopt some integrated research methods to solve the existing problems that decision-makers might encounter when allocating resources in the management and maintenance of heritages and historic buildings.
The purpose of this study is to develop a sustainable decision making model for local governments to resolve these problems. We propose an alternative decision support model to prioritize restoration needs within the limited budgets. The model is constructed based on fuzzy Delphi, fuzzy analysis network process (FANP) and goal programming (GP) methods. In order to avoid misallocate resources; this research proposes a precise procedure that can take multi-stakeholders views, limited costs and resources into consideration. Also, the combination of many factors and goals has been taken into account to find the highest priority and feasible solution results. To illustrate the approach we propose in this research, seven cultural heritages in Taipei city as one example has been used as an empirical study, and the results are in depth analyzed to explain the application of our proposed approach.
Abstract: Multirate multimedia delivery applications in multihop Wireless Mesh Network (WMN) are data redundant and delay-sensitive, which brings a lot of challenges for designing efficient transmission systems. In this paper, we propose a new cross layer resource allocation scheme to minimize the receiver side distortion within the delay bound requirements, by exploring application layer Position and Value (P-V) diversity as well as the multihop Effective Capacity (EC). We specifically consider image transmission optimization here. First of all, the maximum supportable source traffic rate is identified by exploring the multihop Effective Capacity (EC) model. Furthermore, the optimal source coding rate is selected according to the P-V diversity of multirate media streaming, which significantly increases the decoded media quality. Simulation results show the proposed approach improved media quality significantly compared with traditional approaches under the same QoS requirements.
Abstract: It is important to retain customer satisfaction in
information technology services. When a service failure occurs,
companies need to take service recovery action to recover their
customer satisfaction. Although companies cannot avoid all problems
and complaints, they should try to make up. Therefore, service failure
and service recovery have become an important and challenging issue
for companies. In this paper, the literature and the problems in the
information technology services were reviewed. An integrated model
of profit driven for the service failure and service recovery was
established in view of the benefit of customer and enterprise.
Moreover, the interaction between service failure and service recovery
strategy was studied, the result of which verified the matching
principles of the service recovery strategy and the type of service
failure. In addition, the relationship between the cost of service
recovery and customer-s cumulative value of service after recovery
was analyzed with the model. The result attributes to managers in
deciding on appropriate resource allocations for recovery strategies.
Abstract: Low-carbon economy means the energy conservation and emission reduction. How to measure and evaluate the regional low-carbon economy is an important problem which should be solved immediately. This paper proposed the eco-efficiency ratio based on the ecological efficiency to evaluate the current situation of the low-carbon economy in Jiangsu province and to analyze the efficiency of the low-carbon economy in Jiangsu and other provinces, compared both advantages and disadvantages. And then this paper put forward some advices for the government to formulate the correct development policy of low-carbon economy, to improve the technology innovation capacity and the efficiency of resource allocation.
Abstract: Normally business changes are made in order to
change a level of activity in some way, whether it is sales, cash flow,
productivity, or product portfolio. When attempts are made to make
such changes, too often the business reverts to the old levels of
activity as soon as management attention is diverted. Risk
management is a field of growing interest to project managers as well
as in general business and organizational management. There are
several approaches used to manage risk in projects and this paper is a
brief outline of some that you might encounter, with an indication of
their strengths and weaknesses.
Abstract: Resource Discovery in Grids is critical for efficient
resource allocation and management. Heterogeneous nature and
dynamic availability of resources make resource discovery a
challenging task. As numbers of nodes are increasing from tens to
thousands, scalability is essentially desired. Peer-to-Peer (P2P)
techniques, on the other hand, provide effective implementation of
scalable services and applications. In this paper we propose a model
for resource discovery in Condor Middleware by using the four axis
framework defined in P2P approach. The proposed model enhances
Condor to incorporate functionality of a P2P system, thus aim to
make Condor more scalable, flexible, reliable and robust.
Abstract: In the current Grid environment, efficient workload
management presents a significant challenge, for which there are
exorbitant de facto standards encompassing resource discovery,
brokerage, and data transfer, among others. In addition, the real-time
resource status, essential for an optimal resource allocation strategy,
is often not readily accessible. To address these issues and provide a
cleaner abstraction of the Grid with the potential of generalizing into
arbitrary resource-sharing environment, this paper proposes a new
Condor-based pilot mechanism applied in the PanDA architecture,
PanDA-PF WMS, with the goal of providing a more generic yet
efficient resource allocating strategy. In this architecture, the PanDA
server primarily acts as a repository of user jobs, responding to pilot
requests from distributed, remote resources. Scheduling decisions are
subsequently made according to the real-time resource information
reported by pilots. Pilot Factory is a Condor-inspired solution for a
scalable pilot dissemination and effectively functions as a resource
provisioning mechanism through which the user-job server, PanDA,
reaches out to the candidate resources only on demand.
Abstract: In this paper we study the resource allocation problem
for an OFDMA based cooperative two-way relaying (TWR) network.
We focus on amplify and forward (AF) analog network coding
(ANC) protocol. An optimization problem for two basic resources
namely, sub-carrier and power is formulated for multi-user TWR
networks. A joint optimal optimization problem is investigated and
two-step low complexity sub-optimal resource allocation algorithm is
proposed for multi-user TWR networks with ANC protocol. The
proposed algorithm has been evaluated in term of total achievable
system sum-rate and achievable individual sum-rate for each userpair.
The good tradeoff between system sum-rate and fairness is
observed in the two-step proportional resource allocation scheme.
Abstract: One of the determinants of a firm-s prosperity is the
customers- perceived service quality and satisfaction. While service
quality is wide in scope, and consists of various dimensions, there
may be differences in the relative importance of these dimensions in
affecting customers- overall satisfaction of service quality.
Identifying the relative rank of different dimensions of service quality
is very important in that it can help managers to find out which
service dimensions have a greater effect on customers- overall
satisfaction. Such an insight will consequently lead to more effective
resource allocation which will finally end in higher levels of
customer satisfaction. This issue – despite its criticality- has not
received enough attention so far. Therefore, using a sample of 240
bank customers in Iran, an artificial neural network is developed to
address this gap in the literature. As customers- evaluation of service
quality is a subjective process, artificial neural networks –as a brain
metaphor- may appear to have a potentiality to model such a
complicated process. Proposing a neural network which is able to
predict the customers- overall satisfaction of service quality with a
promising level of accuracy is the first contribution of this study. In
addition, prioritizing the service quality dimensions in affecting
customers- overall satisfaction –by using sensitivity analysis of
neural network- is the second important finding of this paper.
Abstract: In Grid computing, a data transfer protocol called
GridFTP has been widely used for efficiently transferring a large volume
of data. Currently, two versions of GridFTP protocols, GridFTP
version 1 (GridFTP v1) and GridFTP version 2 (GridFTP v2), have
been proposed in the GGF. GridFTP v2 supports several advanced
features such as data streaming, dynamic resource allocation, and
checksum transfer, by defining a transfer mode called X-block mode.
However, in the literature, effectiveness of GridFTP v2 has not been
fully investigated. In this paper, we therefore quantitatively evaluate
performance of GridFTP v1 and GridFTP v2 using mathematical
analysis and simulation experiments. We reveal the performance
limitation of GridFTP v1, and quantitatively show effectiveness of
GridFTP v2. Through several numerical examples, we show that by
utilizing the data streaming feature, the average file transfer time of
GridFTP v2 is significantly smaller than that of GridFTP v1.
Abstract: Network management techniques have long been of
interest to the networking research community. The queue size plays
a critical role for the network performance. The adequate size of the
queue maintains Quality of Service (QoS) requirements within
limited network capacity for as many users as possible. The
appropriate estimation of the queuing model parameters is crucial for
both initial size estimation and during the process of resource
allocation. The accurate resource allocation model for the
management system increases the network utilization. The present
paper demonstrates the results of empirical observation of memory
allocation for packet-based services.
Abstract: We discuss the application of matching in the area of resource discovery and resource allocation in grid computing. We present a formal definition of matchmaking, overview algorithms to evaluate different matchmaking expressions, and develop a matchmaking service for an intelligent grid environment.
Abstract: New generation mobile communication networks have
the ability of supporting triple play. In order that, Orthogonal
Frequency Division Multiplexing (OFDM) access techniques have
been chosen to enlarge the system ability for high data rates
networks. Many of cross-layer modeling and optimization schemes
for Quality of Service (QoS) and capacity of downlink multiuser
OFDM system were proposed. In this paper, the Maximum Weighted
Capacity (MWC) based resource allocation at the Physical (PHY)
layer is used. This resource allocation scheme provides a much better
QoS than the previous resource allocation schemes, while
maintaining the highest or nearly highest capacity and costing similar
complexity. In addition, the Delay Satisfaction (DS) scheduling at the
Medium Access Control (MAC) layer, which allows more than one
connection to be served in each slot is used. This scheduling
technique is more efficient than conventional scheduling to
investigate both of the number of users as well as the number of
subcarriers against system capacity. The system will be optimized for
different operational environments: the outdoor deployment scenarios
as well as the indoor deployment scenarios are investigated and also
for different channel models. In addition, effective capacity approach
[1] is used not only for providing QoS for different mobile users, but
also to increase the total wireless network's throughput.
Abstract: In distributed resource allocation a set of agents must assign their resources to a set of tasks. This problem arises in many real-world domains such as distributed sensor networks, disaster rescue, hospital scheduling and others. Despite the variety of approaches proposed for distributed resource allocation, a systematic formalization of the problem, explaining the different sources of difficulties, and a formal explanation of the strengths and limitations of key approaches is missing. We take a step towards this goal by using a formalization of distributed resource allocation that represents both dynamic and distributed aspects of the problem. In this paper we present a new idea for target tracking in sensor networks and compare it with previous approaches. The central contribution of the paper is a generalized mapping from distributed resource allocation to DDCSP. This mapping is proven to correctly perform resource allocation problems of specific difficulty. This theoretical result is verified in practice by a simulation on a realworld distributed sensor network.