Abstract: Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.
Abstract: The goal of data mining algorithms is to discover
useful information embedded in large databases. One of the most
important data mining problems is discovery of frequently occurring
patterns in sequential data. In a multidimensional sequence each
event depends on more than one dimension. The search space is quite
large and the serial algorithms are not scalable for very large
datasets. To address this, it is necessary to study scalable parallel
implementations of sequence mining algorithms.
In this paper, we present a model for multidimensional sequence
and describe a parallel algorithm based on data parallelism.
Simulation experiments show good load balancing and scalable and
acceptable speedup over different processors and problem sizes and
demonstrate that our approach can works efficiently in a real parallel
computing environment.
Abstract: The H.264/AVC standard is a highly efficient video
codec providing high-quality videos at low bit-rates. As employing
advanced techniques, the computational complexity has been
increased. The complexity brings about the major problem in the
implementation of a real-time encoder and decoder. Parallelism is the
one of approaches which can be implemented by multi-core system.
We analyze macroblock-level parallelism which ensures the same bit
rate with high concurrency of processors. In order to reduce the
encoding time, dynamic data partition based on macroblock region is
proposed. The data partition has the advantages in load balancing and
data communication overhead. Using the data partition, the encoder
obtains more than 3.59x speed-up on a four-processor system. This
work can be applied to other multimedia processing applications.
Abstract: Genetic Zone Routing Protocol (GZRP) is a new
hybrid routing protocol for MANETs which is an extension of ZRP
by using Genetic Algorithm (GA). GZRP uses GA on IERP and BRP
parts of ZRP to provide a limited set of alternative routes to the
destination in order to load balance the network and robustness
during node/link failure during the route discovery process. GZRP is
studied for its performance compared to ZRP in many folds like
scalability for packet delivery and proved with improved results. This
paper presents the results of the effect of load balancing on GZRP.
The results show that GZRP outperforms ZRP while balancing the
load.
Abstract: Mobile Ad hoc network consists of a set of mobile
nodes. It is a dynamic network which does not have fixed topology.
This network does not have any infrastructure or central
administration, hence it is called infrastructure-less network. The
change in topology makes the route from source to destination as
dynamic fixed and changes with respect to time. The nature of
network requires the algorithm to perform route discovery, maintain
route and detect failure along the path between two nodes [1]. This
paper presents the enhancements of ARA [2] to improve the
performance of routing algorithm. ARA [2] finds route between
nodes in mobile ad-hoc network. The algorithm is on-demand source
initiated routing algorithm. This is based on the principles of swarm
intelligence. The algorithm is adaptive, scalable and favors load
balancing. The improvements suggested in this paper are handling of
loss ants and resource reservation.
Abstract: Recently, there have been an increasing interest in RFID system and RFID systems have been applied to various applications. Load balancing is a fundamental technique for providing scalability of systems by moving workload from overloaded nodes to under-loaded nodes. This paper presents an approach to adaptive load balancing for RFID middlewares. Workloads of RFID middlewares can have a considerable variation according to the location of the connected RFID readers and can abruptly change at a particular instance. The proposed approach considers those characteristics of RFID middle- wares to provide an efficient load balancing.
Abstract: Wireless LAN (WLAN) access in public hotspot areas
becomes popular in the recent years. Since more and more multimedia
information is available in the Internet, there is an increasing demand
for accessing multimedia information through WLAN hotspots.
Currently, the bandwidth offered by an IEEE 802.11 WLAN cannot
afford many simultaneous real-time video accesses. A possible way to
increase the offered bandwidth in a hotspot is the use of multiple access
points (APs). However, a mobile station is usually connected to the
WLAN AP with the strongest received signal strength indicator (RSSI).
The total consumed bandwidth cannot be fairly allocated among those
APs. In this paper, we will propose an effective load-balancing scheme
via the support of the IAPP and SNMP in APs. The proposed scheme is
an open solution and doesn-t need any changes in both wireless stations
and APs. This makes load balancing possible in WLAN hotspots,
where a variety of heterogeneous mobile devices are employed.
Abstract: A catastrophic earthquake measuring 6.3 on the
Richter scale struck the Christchurch, New Zealand Central Business
District on February 22, 2012, abruptly disrupting the business of
teaching and learning at Christchurch Polytechnic Institute of
Technology. This paper presents the findings from a study
undertaken about the complexity of delivering an educational
programme in the face of this traumatic natural event. Nine
interconnected themes emerged from this multiple method study:
communication, decision making, leader- and follower-ship,
balancing personal and professional responsibilities, taking action,
preparedness and thinking ahead, all within a disruptive and uncertain
context. Sustainable responses that maximise business continuity, and
provide solutions to practical challenges, are among the study-s
recommendations.
Abstract: This paper presents a novel control strategy of a threephase
four-wire Unified Power Quality (UPQC) for an improvement
in power quality. The UPQC is realized by integration of series and
shunt active power filters (APFs) sharing a common dc bus capacitor.
The shunt APF is realized using a thee-phase, four leg voltage source
inverter (VSI) and the series APF is realized using a three-phase,
three leg VSI. A control technique based on unit vector template
technique (UTT) is used to get the reference signals for series APF,
while instantaneous sequence component theory (ISCT) is used for
the control of Shunt APF. The performance of the implemented
control algorithm is evaluated in terms of power-factor correction,
load balancing, neutral source current mitigation and mitigation of
voltage and current harmonics, voltage sag and swell in a three-phase
four-wire distribution system for different combination of linear and
non-linear loads. In this proposed control scheme of UPQC, the
current/voltage control is applied over the fundamental supply
currents/voltages instead of fast changing APFs currents/voltages,
there by reducing the computational delay and the required sensors.
MATLAB/Simulink based simulations are obtained, which support
the functionality of the UPQC. MATLAB/Simulink based
simulations are obtained, which support the functionality of the
UPQC.