ns2 project in Hawaii

ns2 project in Hawaii

        ns2 project in Hawaii on the other hand, a dynamic approach for the event-distribution and state-information-updates  would lead to additional communication and management overheads. In some scenarios, the communication cost of list-updates or fine-grained events’ communication between a dynamically ns2 project in Hawaii variable set of components, could make attractive a complementary approach. As an example,

when the system communication infrastructure is

characterized by significant performance ns2 project in Hawaii asymmetry (e.g.

shared memory vs. LAN communication), like in

networked clusters of PCs, the migration cost needed to

dynamically cluster the set of interacting ns2 project in Hawaii components

over a single Physical Execution Unit (PEU) could

become attractive. This would be even more attractive if

the following three assumptions could be satisfied: i)

components’ migration could be ns2 project in Hawaii implemented

incrementally as a simple data-structure (i.e. state)

transfer, ii) the component state would ns2 project in Hawaii be comparable

with the amount of data exchanged for interactions, and

iii) the object interaction scheme would be maintained for a significant time In the following, as an example of a dynamically variable system, we focus on a wireless multi-hop Mobile ns2 project in Hawaii Ad Hoc Network (MANET) [17, 35]. Simulation models for wireless systems incarnate the assumptions that motivated

our design. The number of simulated hosts in our ns2 project in Hawaii expectations can reach high values, requiring the

simulation of massively populated scenarios. Topology changes due to simulated hosts’ mobility map on

causality effects in the “areas of influence” of each mobile device, resulting in dynamically shaped ns2 project in Hawaii causalitydomains and component interaction schemes. Given two or ns2 project in Hawaii more neighbor-hosts sharing the wireless medium, the causal effect of signal interference could result in a chain of local-state events up to the high ns2 project in Hawaii protocols’ layers [35]. In our approach, we define a model entity as the data

structure defined to model a Simulated Mobile Host

(SMH). A certain degree of time-locality of ns2 project in Hawaii local

communication can be considered an acceptable

assumption in many wireless system models, depending

on the communication load and the ns2 project in Hawaii mobility model


ns2 project in Missouri

ns2 project in Missouri

     ns2 project in Missouri paper structure is the following: in section 2 we

outline some concepts about the distributed simulation of

dynamic models, specifically, the wireless ad hoc

networks; in section 3 the key issues for the ns2 project in Missouri ARTÌS and

GAIA framework implementation and the proposed

migration heuristics are defined; in section 4 a prototype

wireless system’s model and a preliminary set of

simulation results are presented; in section 5 we

summarize our conclusions and future ns2 project in Missouri work. We define a dynamic system as a system where the

interactions (i.e. the causal effects of events) are

dynamically subject to fast changes driven by the system

(and model) evolution over the simulated time. Given this ns2 project in Missouri general definition, a wireless network can be an example of a highly dynamic system.

To realize a correct evolution under the event-causality

viewpoint, every model components’ interaction should

be notified as an event-message to all the causally

dependent model components, by a runtime ns2 project in Missouri eventmessage

distribution mechanism. Complex systems with detailed and fine-grained ns2 project in Missouri simulation models can be considered communication-intensive under the distributed simulation approach. As a result, interprocess

communication may become the bottleneck of the distributed simulation paradigm. The way interprocess

communication can be sustained in distributed systems

would depend mainly on the execution units and on the communication ns2 project in Missouri support, that is, on the simulation system resources, architectures and characteristics. As an

example, message passing communication can be performed ns2 project in Missouri efficiently over shared memory architectures, while it would require medium and high communication

latencies over local and wide area network communication services. It is self evident how the

physical clustering of interacting model components on a shared memory architecture could result in the advantage to exploit the most efficient message passing

implementation. Unfortunately, in highly dynamic systems any ns2 project in Missouri optimal static clustering and allocation,

based on the current component-interaction scheme, will

become immediately suboptimal, due to the dynamics of

the model interactions. The approach used in currently available ns2 project in Missouri implementations is to consider the model component interactions, by adapting the event message distribution accordingly. No background optimization is based on the heterogeneity of available communication

infrastructure characteristics. In presence of a ns2 project in Missouri dynamic system, the event-message distribution of a distributed simulation requires a dynamic ns2 project in Missouri definition of publishing/subscribing lists, or the implementation of a complete state-sharing information


ns2 project in Territories

ns2 project in Territories

        ns2 project in Territories this environment we

designed the parallel processing program on a parallel

computer clusters based on the programming rules of the

JIAJIA to process RS data through logical database ns2 project in Territories on the

background. JIAJIA is a virtual memory sharing (SVM) software

platform. The design of the parallel program should follow the

below rule. 1) It must be a SPMD (Single Program Multiple Data)

program structure that runs on all computers and ns2 project in Territories operates on different data. 2) It should adopt the memory sharing based programming, in which the sharing variable is exclusive in the

whole system and is shared by all computers and the private variable exists ns2 project in Territories in a single process and can only be accessed by one computer individually.

Image Extract: Background server calls the corresponding database table

based on the users’ request parameters such as information of

the image file, the wave band, the time, the region and so on.

2) Image Matching: Sewing up the overlapping tiles in the edges ns2 project in Territories of two

images[8]. 3) Image compressing: Compressing the extracted image into JPEG format,In this paper we ns2 project in Territories completed the application and experiment analysis on the efficiency of the SVM-based parallel servers

and the parallel program. The experiment environment is an Intranet that includes a parallel ns2 project in Territories computer clusters. Every computer in the intranet is a P

ns2 project in Denmark

ns2 project in Denmark

        ns2 project in Denmark the programming interface based on sharing virtual

memory (or called SVM) can be implemented by software

through message transfer upon hardware in the sharing storage

multi-processing, which changes native storages ns2 project in Denmark of different

nodes into one complete logical entity to provide user with storage access [3].

In this paper the background server is an SVM-based

parallel common computer cluster, which uses SVM to

implement parallel processing. Now the SVM ns2 project in Denmark software

systems include Midway, Munin, TreadMarks, JIAJIA and so

on. As SVM combines the advantages of the simple

programming of sharing memory multi-processing ns2 project in Denmark system and

easy realization of message-transferring multi-computer

system, it has been studied more and more [3]. The study on

the parallel Remote Sensing database system in this paper is

based on the JIAJIA parallel platform (The Memory

Organization and Calling of JIAJIA is shown in Figure1). The

RS data processing in the system follows the rule of JIAJIA,

which includes the rule of memory distribution and calling,

the rule of program synchronization, the rule of burden

balance and the rule of message transfer. The rational ns2 project in Denmark storage and organization of RS data on the

server is the first requirement to implement issuance through

Internet. The research result stated bellow has realized the

management of huge volume of RS data by commercial

database management software and its issuance.

A. Solid index mechanism for the multi-sensor ns2 project in Denmark remote

sensing data To organize RS data on the parallel servers, a solid index

mechanism of ‘pyramid, block, layer, and epoch’ (as shown in

Figure 2.) is adopted in this paper according to the property of

the RS data. With the mechanism the logical database for

multi-sensor, multi-resolution, multi-spectrum ns2 project in Denmark and multi-epoch

RS data can be built up The adoption of solid index mechanism of ‘pyramid, block,

layer, epoch’ can build the RS data logical database to

construct the corresponding relationship between the database

and RS data files. In contrast to the real data file, the ns2 project in Denmark index

database is an abstract, virtual, logical database, which can be

used to manage huge volume of RS data with current

commercial RDBMS. The design of the logical database is ns2 project in Denmark to organize the tables

and fields of the database according to the solid index

mechanism of ‘pyramid, block, layer, epoch’ and the

information set for user search. Thus the relationship between

the database and RS data files can be created. At the same time,

the logical database can organize all database tables well and

build the logical relationship between the tables to increase the

research speed Once the multi-sensor RS data ns2 project in Denmark is organized logically, the

data files and the logical database can be stored in different

computer nodes in a computer group.

ns2 project in Wyoming

ns2 project in Wyoming

        ns2 project in Wyoming more detailed experiment results and comparisons

with MPI can be found in [23]. As described earlier, JOPI

utilizes the middleware infrastructure; however, the experiments

show that the agents impose a very small ns2 project in Wyoming overhead

while providing efficient and flexible functions for JOPI. In

addition, the communication overhead incurred by the

agent occurs mostly with the initial deployment ns2 project in Wyoming of the

application, which then relies on the programming model’s

implementation of the interprocess communication functions.

The agents also allow user jobs to be deployed and

executed on remote machines transparently, requiring no

user involvement other than specifying the number of

processors needed. This, in addition to Java’s ns2 project in Wyoming portability,

has allowed easy utilization of multiple distributed platforms

of different specifications to execute a single parallel

application. The middleware infrastructure provides services to support

the development of high-performance parallel and distributed

Java applications on clusters and heterogeneous

systems. The distributed agents collectively ns2 project in Wyoming form the

middleware infrastructure that supports different parallel

programming models, in addition to distributed applications.

The middleware provides APIs that enable programming

models developers to build different parallel

programming models and tools. In addition, the ns2 project in Wyoming middleware

allows the distributed/parallel application developers

to build, deploy, monitor, and control their applications,

which can be written using the middleware directly or the

programming models provided on top of it. Some of the Portability: The system ns2 project in Wyoming is fully portable, allowing it

to support seamless execution of parallel applications

across different multiple platforms. Here, the

agents distribute user processes to remote machines,

deploy them remotely as threads, monitor their

progress, and allow users to manage and control

their applications. 2. Expandability: The hierarchical structure allows

easy additions/removals of agents from the system

transparently from the programming models and

applications. It is easy to modify or replace the ns2 project in Wyoming systems

components such as the scheduler and deployment

mechanisms, and add more features such ns2 project in Wyoming as fault

tolerance and resource discovery without requiring changes to the ns2 project in Wyoming applications or the programming models. The programming model implemented using the middleware is also free to utilize some or

all of the functions provided by the middleware, while utilizing its own ns2 project in Wyoming specialized functions as well. Agents, collectively, have information ns2 project in Wyomingabout all the resources, which provides a distributed information base of system resources.

Thus, they can collaborate to provide efficient and comprehensive ns2 project in Wyoming resource discovery and management

ns2 project in Mississippi

ns2 project in Mississippi

         ns2 project in Mississippi the main reason for

this is that parallel applications utilize the middleware to

deploy and start execution, but then they execute independently

from the agents except in few special cases. The algorithm ns2 project in Mississippi is based on branch-and-bound search [21].

This problem required using many of JOPI’s primitives to

implement an efficient load-balanced solution. Broadcast

was used to distribute the original problem ns2 project in Mississippi object to

processes and to broadcast the minimum tour value found,

thus allowing other processes to update their minimum

value to speedup their search. Asynchronous ns2 project in Mississippi communication

is used by processes to overlap the reporting of their

results to the master with other tasks. The results, as shown

in Fig. 3, show good speedup with growing ns2 project in Mississippi number of

processors and fixed problem size.

6.1.3 Experiments on Heterogeneous Platforms

These experiments show the capabilities of the middleware

to support the execution of parallel applications on

heterogeneous platforms with minimum user ns2 project in Mississippi  involvement.

All experiments used standard JVM sdk CSNT: 3 CPUs, Intel x86 700MHz, 1.5GB RAM, OS:

Windows 2000 advanced server.

. RCF: SGI Origin 2000, 32 processors, 250 MHz, 4MB

cache, 8GB RAM, OS: IRIX 6.5.13.

. Sandhills: Cluster, 24 nodes, dual 1.2 MHz AthlonMP,

256KB cache, 1GB RAM, OS: Linux. To fairly compare the performance, the sequential

running time for the program was measured on ns2 project in Mississippi each

platform. Speedup is calculated with respect to the fastest sequential time in the configuration used. A more formal

model to calculate the performance of parallel applications

on heterogeneous systems can be found in A dense ns2 project in Mississippi matrix multiplication (MM) algorithm [17] is used with load balancing

mechanism and synchronous point-to-point ns2 project in Mississippi communication. A matrix of size 1; 800 _ 1; 800 floating numbers was

used, with a stripe size of 300 rows or columns.

The algorithm used is the same as in Section 6.1.2, using the machines CSNT

and Sandhills. TSP was executed for 22 cities using different

configurations of heterogeneous processors from Sandhills The ns2 project in Mississippi infrastructure ns2 project in Mississippi provides a platform for parallel Java

using JOPI, which achieves good performance. However,

JOPI, in its current form, is most suitable for applications

that have high computation to communication ratio or

coarse grain parallelism, but can be optimized to handle

finer grain parallelism. In addition, the varying specifications

of the processors used indicate the possibility ns2 project in Mississippi of

achieving more speedup and faster response times by

distributing tasks based on their suitability to the platform.

For example, if some tasks require excessive ns2 project in Mississippi data sharing,

they can be assigned to a multiprocessor parallel machine,

while relatively independent tasks can be assigned to a


ns2 project in Georgia

ns2 project in Georgia

       ns2 project in Georgia although the linear mode of operation is efficient with small clusters because no overhead is imposed from the structure, with the hierarchical structure on large clusters, most agent operations are performed in parallel resulting in faster response times. The hierarchical structure also provides

other advantages such as: 1. providing scalable mechanisms to easily expand the

system, 2. providing the update and recovery ns2 project in Georgia mechanisms for

automatic detection of agent failures or change of

status/resources and techniques to report errors and

adapt to changes, 3. providing routing capabilities in the leaders to

facilitate process communications across ns2 project in Georgia multiple

platforms over multihop links, and

4. making the agents management and ns2 project in Georgia monitoring

operations more efficient and less dependant on the

full connectivity of the system.

The middleware infrastructure is capable ns2 project in Georgia of supporting

different parallel programming models. An example of this

support is the implementation of the Java Object-Passing

Interface (JOPI) [23]. In addition, distributed applications

utilize this middleware infrastructure ns2 project in Georgia to facilitate their

operation. In this section, we discuss JOPI, which provides

APIs similar to MPI and facilitates information exchange

using objects. It utilizes the features provided by the

middleware, including the scheduling ns2 project in Georgia mechanisms, remote

deployment and execution of user classes, control of user

threads and available resources, and the security mechanisms.

In addition, JOPI was designed such that processes

communicate directly with one another if all job threads are

directly connected. Otherwise, the threads utilize the

agents’ routing capabilities. Benchmark ns2 project in Georgia programs were written to evaluate the performance

of the system using JOPI. All experiments, unless

otherwise mentioned, were conducted on Sandhills, a

cluster of 24 Dual 1.2 GHz AMD-processor nodes, 256 KB

cache per processor, and 1 GB RAM per node. The cluster is

connected via a 100 Mbps Ethernet. For these experiments,

standard JVM sdk 1.3.1 was used. To test the agent overhead, Java programs were executed

independently (without the agent) and then through the

agent. The average execution time for both executions were

measured and compared. Currently, a small ns2 project in Georgia overhead

(around 0.37 percent) was found since the agent is very

lightweight. We assume that adding more functions to the

agent may introduce additional, but relatively minor delays.

In addition, the overhead is relatively ns2 project in Georgia independent from the

application, thus it will increase only as ns2 project in Georgia the number of

processors or machines used increases.

ns2 project in Oregon

ns2 project in Oregon

        ns2 project in Oregon in addition, Lx informs all other

leaders of the changes to avoid the failed node

Within the affected cluster, jobs that do not involve the

failed node continue normally. However, jobs involving the

failed node will fail unless they utilize their own fault

tolerance mechanisms. The protocol’s distributed ns2 project in Oregon nature

makes it possible for more than one leader to try to restore

the same failed leader. However, due to the ns2 project in Oregon asynchronous

execution of the recovery protocol, the probability of

multiple leaders simultaneously initiating ns2 project in Oregon the leader recovery

protocol is very low. In addition, a back off mechanism

can be devised so that a leader can decide ns2 project in Oregon whether to

continue the protocol or stop because another leader has

already started it. One possible approach is to use the leader

ID such that the leader with the higher ID proceeds with the

leader recovery protocol, while others stop. However, in

case more than one leader starts the ns2 project in Oregon protocol at the same

time, an active agent ignores new activation messages, thus

will not be affected by the duplication. Moreover, the

leaders will eventually receive the broadcast LNRM and

respond to it, resulting in all but one leader to terminate the

leader recovery protocol. This protocol is used to report changes in the available

resources within a cluster or virtual cluster. The protocol is

triggered if one or more nodes (other than the head node) in

the cluster fail. When a leader Lx does not ns2 project in Oregon receive a

response from a descendant agent, then Lx, Pings the node of that agent to see if it is up and

running and still connected to the network.

2. If it is up, then Lx tries to remotely reactivate the

agent on that node using the AAM.

3. If the node does not respond, then Lx

a. reports the problem to the ns2 project in Oregon administrator,

b. excludes the node from the cluster or virtual


c. updates the leader’s resources information, and

d. informs all other nodes on the cluster or virtual

cluster of the changes.

4. If the node is restored later, the ns2 project in Oregon agent on that node

informs the leader of its recovery and updates the

cluster and itself with the local routing information.

Jobs using the failed node will fail unless ns2 project in Oregon they utilize

their own fault tolerance mechanisms. In addition, the

protocol provides an automatic mechanism for new or

recovered nodes to be included back in the system. In this

case, the highest incurred cost comes from activating the agent ns2 project in Oregon and updating the clusters information. Nevertheless, this only occurs once per reactivated agent. In addition, the overhead here is limited to the cluster or virtual cluster to

which the failed node belongs, thus it does not have any effects on the rest ns2 project in Oregon of the system. With the hierarchical structure, the operations of the agents are more organized and efficient compared to having a linear structure where all nodes must see all other nodes at all times. The hierarchical structure also ns2 project in Oregon utilizes automatic startup and configuration mechanisms and dynamic agent allocations that reduce user involvement

ns2 project in Tennessee

ns2 project in Tennessee

       ns2 project in Tennessee the success of this and other protocols and the proper

functionality of the agents rely on having a suitable naming

(identification) scheme for the agents. Many ns2 project in Tennessee mechanisms

can be used; however, for the system to be scalable, the

naming scheme needs to be scalable also. One suitable

scheme is the hierarchical naming used for the Internet.

Here, the leaders on the top level of the ns2 project in Tennessee hierarchy take a

common root name followed by each machine/cluster

name. The next levels use their leader’s name as a prefix

to their names. For example, assume that the ns2 project in Tennessee structure

shown in Fig. 2 belongs to UNL and, then, the top-level

leaders can be UNL.L1, UNL.L2, and UNL.L3. Leader 4 is

then called UNL.L3.L4 and the agents under leader 2, for example, are called UNL.L2.A1, UNL.L2.A2, etc. Such a

scheme, while potentially complicated for ns2 project in Tennessee a small system,

allows the system to systematically grow without any need

to change previously assigned names or the ns2 project in Tennessee naming scheme

itself. This also allows agents to use the machines’ actual

Internet URLs as their names, thus allowing ns2 project in Tennessee  easy access

through the Internet. Adopting this scheme, however,

requires some form of neighbor discovery ns2 project in Tennessee mechanism as

in IPv6 [14] to ensure the use of unique names for the

participating agents. In general, the overhead incurred in

constructing a hierarchical structure is relatively high, thus

it may not benefit a system with a small number of nodes.

However, it is essential in two environments:

1. The system is composed of multiple ns2 project in Tennessee smaller

systems (clusters, NOW, multiprocessor machines,

etc.) that do not have full connectivity to all their

nodes. Thus, the head node in each subsystem is

assigned a leader that is responsible of connecting

it to other subsystems. 2. The system includes ns2 project in Tennessee  very large clusters comprising

tens/hundreds of nodes, thus accessing all nodes in

a linear fashion is very time consuming. Here, the

threshold needs to be selected to optimize the

utilization of the suitable structure. Analytical

models or experimental evaluations can be used to

select that value. This protocol is used in case a ns2 project in Tennessee leader fails to respond to an

AM message sent by another leader. If a leader Lx at one

level times out before receiving an AMA response from

another leader, say Ly, the following steps are taken by Lx

to try to recover from the problem. 1. Lx broadcasts the problem to all other leaders at the

same level using the LNRM and informs them that it

will try to solve the problem. 2. Lx pings the node/machine where Ly resides to see

if it is connected and up. 3. If the node is still up, then a. Lx initiates a remote agent activation command

to reactivate the agent using the AAM and b. when the new agent is up, Lx activates it as a

leader and sends it all relevant leader information. The new leader, Ly, uses the startup

protocol to restore its information. 4. If the agent does not ns2 project in Tennessee reinitialize (e.g., has been

deleted from the node) or the node does not respond if a connection exists to another node in the

cluster, Lx activates that node’s agent as a

leader. The new leader then assumes ns2 project in Tennessee its new

role and updates its routing and resource

information using the startup protocol,

b. if no connection exists, Lx reports the problem to

the administrator and excludes all routing

information to the cluster led by Ly from the

routing tables.

ns2 project in New Hampshire

ns2 project in New Hampshire

       ns2 project in New Hampshire one suitable example is the contentbased

object routing technique called Java

Object Router Each agent should a. on activation (by receiving an AAM), find and

register local node resources information. Resources

include available CPUs, CPU power,

ns2 project in New Hampshire storage and memory capacity, etc., b. respond to the leader with an AMA message

containing the agent’s ID, address, and resources

information, and c. receive and locally update the neighbors’ addresses

from the leader for future ns2 project in New Hampshire interprocess

communication. When information becomes available, agents and leaders

communicate through the created hierarchical structure

where agents collaborate to satisfy user job ns2 project in New Hampshire requirements

efficiently. The periodic availability checks can be finetoned

to the system properties to minimize the number of

checks performed. This mainly relies on the stability of the

system used. If the system is stable and has low probability

of failures, then the period between checks can be set to be

long, thus reducing the total messages ns2 project in New Hampshire exchanged. However,

if the system includes unreliable components or is

connected through unreliable communications links, the

period should be short enough to discover failures and

recover quickly to minimize job failures.

5.3 Leader Startup Protocol

This protocol is designed to assist in automating the startup

and configuration of leader agents. The outcome ns2 project in New Hampshire of this

protocol is to have leaders acquire full resource information

about their descendant agents (including virtual clusters)

and routing information about other leaders. In addition, all

agents within the same cluster (or virtual cluster) need ns2 project in New Hampshire to have address information of their leader and that of one another. Another important aspect of this protocol is ns2 project in New Hampshire that it allows agents and leaders to be easily added to the system with minimum user intervention. The protocol works as

follows: 1. The new leader, Lx, constructs an LAM with its information and ns2 project in New Hampshire broadcasts it on the network. 2. On receiving LAM from Lx, a leader registers received ID and address and sends LAAM to Lx. 3. On receiving the LAAM, Lx updates the address and routing information. 4. Lx initializes the resource table to its local node’s

available resources and remotely starts accessible agents on the cluster or networked ns2 project in New Hampshire system by broadcasting an AAM. 5. On receiving the AAM from Lx, an agent starts up, constructs an AMA, and sends it to Lx.

6. On receiving an AMA from an agent, Lx updates the

resources and routing information. 7. If the number of agents activated is higher than a

preset threshold, Lx activates one of the agents to be a leader and assigns some of the agents as its descendants. The new leader performs all the leader

operations for the agents under its control.

8. Step 7 is repeated as necessary to evenly distribute agents and leaders to ns2 project in New Hampshire form a balanced hierarchical

structure of agents.