Self-attention has recently been adopted for a wide range of sequence modeling problems. Despite its effectiveness, self-attention suffers from quadratic computation and memory requirements with respect to sequence length. Successful approaches to re
duce this complexity focused on attending to local sliding windows or a small set of locations independent of content. Our work proposes to learn dynamic sparse attention patterns that avoid allocating computation and memory to attend to content unrelated to the query of interest. This work builds upon two lines of research: It combines the modeling flexibility of prior work on content-based sparse attention with the efficiency gains from approaches based on local, temporal sparse attention. Our model, the Routing Transformer, endows self-attention with a sparse routing module based on online k-means while reducing the overall complexity of attention to O(n1.5d) from O(n2d) for sequence length n and hidden dimension d. We show that our model outperforms comparable sparse attention models on language modeling on Wikitext-103 (15.8 vs 18.3 perplexity), as well as on image generation on ImageNet-64 (3.43 vs 3.44 bits/dim) while using fewer self-attention layers. Additionally, we set a new state-of-the-art on the newly released PG-19 data-set, obtaining a test perplexity of 33.2 with a 22 layer Routing Transformer model trained on sequences of length 8192. We open-source the code for Routing Transformer in Tensorflow.1
Many wireless sensor network applications like forest fire detection and environment monitoring recommend making benefit from moving humans, vehicles, or animals to enhance network performance. In this research, we had improved our previous protocol
(Dynamic Tree Routing DTR) to support mobility in a wireless sensor network. First, we had mathematically approximated the speed threshold for mobile sensors, which enables them to successfully associate with nearby coordinators. Second, we test our (MDTR) protocol in a network with mobile sensors sending packets toward the network's main coordinator. The simulation results obtained from network Simulator (NS2) showed a good approximation of speed threshold, and good performance of MDTR in term of delay, throughput, and hop-count compared with AODV and MZBR Protocols.
Today, MANET networks have attracted the attention of many researchers in the
field of communications and networks because of the ease of establishing such networks
and their wide spread in the various scientific and applied fields. The researchers
have
proposed many routing protocols in these networks. This is because the goal of the
development process is to make these networks more secure and stable because they are
highly vulnerable to penetration by any other node located in the perimeter of the network
because the security factors are weak.
These protocols are categorized according to its strategy to three types are the
proactive class, which relies on the transmission of control messages over the network to
update the routes between any two nodes, and the reactive class, which depends on
discovering the route when needed, without broadcasting of control messages across
network , And the hybrid type, which combines the two classes, that divides the network
into clusters where the nodes interconnections within the cluster depends on the interactive
method, while the transmission between two nodes that belong to different clusters is
depend on proactive method.
In this research, the MANET network was simulated by subjecting the packet
generation process to an exponential probability distribution with the change of the value
of the (α) parameter in order to obtain the best performance when the number of nodes
changed taking into account the parameters of Throughput, load and delay.
Many wireless sensor network applications like forest fire detection and environment
monitoring recommend making benefit from moving humans, vehicles, or animals to
enhance network performance. In this research, we had improved our previous protoco
l
(Dynamic Tree Routing DTR) in order to support mobility in a wireless sensor network.
First, we had mathematically approximated the speed threshold for mobile sensors, which
enables them to successfully associate with nearby coordinators. Second, we test our
(MDTR) protocol in a network with mobile sensors sending packets toward network's
main coordinator. The simulation results obtained from network Simulator (NS2) showed a
good approximation of speed threshold, and good performance of MDTR in term of delay,
throughput, and hop-count compared with AODV and MZBR Protocols.
In this PAPER, we perform a study and extensive comparative between
the well-known link quality estimators and CTP, a tree-based routing
protocol provided by TinyOS for different network topology and simulate
it using TOSSIM simulator to evaluate
the performance of these
estimators.
This research identifies
some improved protocols which support multiple paths between
source and destination.
Mobile wireless sensor network (MWSN) is a wireless ad hoc network that consists
of avery large number of tiny sensor nodes communicating with each other in which
sensornodes are either equipped with motors for active mobility or attached to mobile
objectsfor passive mobility. A real-time routing protocol for MWSN is an exciting area of
research
because messages in the network are delivered according to their end-to-end
deadlines
(packet lifetime) while sensor nodes are mobile. This paper proposes an enhanced
realtime
with load distribution (ERTLD) routing protocol for MWSN which is based on our
previousrouting protocol RTLD. ERTLD utilized corona mechanism and optimal
forwardingmetrics to forward the data packet in MWSN. It computes the optimal
forwarding nodebased on RSSI, remaining battery level of sensor nodes and packet
delayover one-hop. ERTLDensures high packet delivery ratio and experiences minimum
end-to-end delay in WSNand MWSN compared to baseline routing protocol. . In this paper
we consider a highly dynamic wireless sensor network system in which the sensor nodes
and the base station(sink) are mobile.ERTLD has been studied and verified and compared
with baseline routing protocols RTLD,MM-SPEED , RTLCthrough Network Simulator-
2(NS2)
شبكات الحساسات اللاسلكية
RTLD (Real-time with load distributed routing) Protocol
شبكات الحساسات اللاسلكية النقالة
بروتوكول التوجيه بالزمن الحقيقي مع توزيع الحمولة
بروتوكول التوجيه بالزمن الحقيقي المحسن مع توزيع الحمولة
معدل استقبال الرزمة
خيار التوجيه الأفضل
مؤشر قوة الاشارة المستقبلة
WSN(wireless sensor networks)
MWSN) Mobile wireless sensor networks)
ERTLD ( Enhanced Real-time with load distributed routing) Protocol
PRR(Packet Reception Rate)
Optimal Forwarding (OF)
RSSI: Received Signal Strength Indicator
MN(Mobile Node)
MS(Mobile sink)
المزيد..
In this research, we are studying the possibility of contribution in solving the Vehicle
Routing Problem with Time Windows(VRPTW),that is one of the optimization problems
of the NP-hard type.
Moreover, Hybrid algorithm (HA) provided that integrate
s between Tabu Search
Algorithm and Guided Local Search algorithm And existence 2- Opt Local Search, based
on the savings algorithm in terms of continued of a particular objective to provide a lot of
savings. As we will compare the presented approach with standard tests to demonstrate
the efficiency, and their impact on the quality of the solution in terms of speed of
convergence and the ability to find better solutions.
Routing protocols play an essential role in meeting the quality of service
requirements in the network, but achieving these requirements may require frequent send
and receive operations to build and maintain routing tables, which consume sensors
r
esource If we take into consideration the limitations of wireless sensor networks in terms
of the amount of available energy and storage capacity.
In this research a performance comparison of the on-demand Distance Vector
Routing protocol AODV and Hierarchical Routing protocolHR was carried out in terms of
the packet delivery and loose rate, delay and jitter, and the amount of expended energy in
the Wireless sensor network operates according to IEEE802.15.4 standard in cases where
some of sensors get out of work for limited periods of time.
The results showed that the hierarchical routing protocols perform better in terms of
delay time and transfer rate and the amount of consumed energy than on-demand Distance
Vector Routing protocol routing protocol, but suffer larger packet loss due to routing path
corruption as a result of sensors crashes.
In this research, we are studying the possibility of contribution
in solving the multi-objective vehicle Routing problem with time
windows , that is one of the optimization problems of the NP-hard
type , This problem has attracted a lot of attenti
on now because of
its real life applications.
Moreover, We will also introduced an algorithm called hybrid
algorithm (HA) which depends on integrates between Multiple
objective ant colony optimisation (MOACO) and tabu search (TS)
algorithm based on the Pareto optimization , and compare the
presented approach is the developer with standard tests to
demonstrate the applicability and efficiency.
