This document provides an overview and summary of networking technologies for Internet of Things applications. It discusses the roles and functions of network modules, common routing techniques like flooding, distance vector routing, and source routing. It then describes two specific routing protocols - Ad Hoc On-demand Distance Vector (AODV) routing and the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). AODV uses an on-demand approach to route discovery, while RPL is a proactive protocol that constructs a destination-oriented directed acyclic graph to route packets from nodes to the root. The document also discusses topology maintenance and the use of Trickle timers in RPL.
Default and On demand routing - Advance Computer NetworksSonali Parab
Routing is the process of selecting best paths in a network. In the past, the term routing was also used to mean forwarding network traffic among networks. However this latter function is much better described as simply forwarding. Routing is performed for many kinds of networks, including the telephone network (circuit switching), electronic data networks (such as the Internet), and transportation networks.
In packet switching networks, routing directs packet forwarding (the transit of logically addressed network packets from their source toward their ultimate destination) through intermediate nodes. Intermediate nodes are typically network hardware devices such as routers, bridges, gateways, firewalls, or switches. General-purpose computers can also forward packets and perform routing, though they are not specialized hardware and may suffer from limited performance. The routing process usually directs forwarding on the basis of routing tables which maintain a record of the routes to various network destinations. Thus, constructing routing tables, which are held in the router's memory, is very important for efficient routing. Most routing algorithms use only one network path at a time. Multipath routing techniques enable the use of multiple alternative paths.
Comparison of different MANET routing protocols in wireless ADHOCAmitoj Kaur
In this project, AODV and Flooding routing protocols using different parameter metrics have been simulated and analyzed
Simulation results show that performance parameters of the routing protocols may vary depending on network load, mobility and network size.
Under G-Sense Model, AODV experience the highest Packet Delivery Fraction and Throughput with the increase of nodes stop time, and mobile nodes number.
AODV and Simple Flooding performance is due to their on demand characteristics to determine the freshness of the route. And it is proved also that AODV has a slightly higher Average end-to-end Delay than Simple Flooding.
Comparative Analysis of MANET Routing Protocols and Cluster Head Selection Te...IJERA Editor
Mobile Ad-hoc Network is a kind of wireless network. It is a backbone of new generation advanced communication technology. MANET is an ideal applicant for rescue and emergency situation due to its independence of connected devices of fixed wires. This paper represents a work on trust based system in MANET cluster that can be used to improve the performance of the network even in the existence of not trusted nodes. In the cluster architecture, cluster head and gateway nodes form a communication for routing among neighbouring clusters. But selection of cluster head is the important problem in dynamic Ad-hoc network because cluster head work as coordinator in clustered architecture. In this work, some values have used correspond to the threshold values of forward packet and dropped packet of each node within the network cluster. These values have been used dynamically updated every time and the node is selected as cluster head. In this technique of selecting the node as cluster head, the node which has maximum trusted value is elected as cluster head and this information is updated in every node’s trusted table. After implementation of our desired work, the proposed Dynamic Trust Evaluation of Cluster Head (DTE-CH) technique is analysed with traditional routing protocols and traditional clustering technique viz. Highest Degree Algorithm. The simulation is done by using network simulator software on the basis of different performance metrics throughput, packet delivery ratio, routing overhead, packet drop, average end to end delay and remain energy. Simulation result presents that proposed DTE-CH technique improves the performance of network as compare to most suitable existing AODV MANET protocol based technique as well as traditional highest degree clustering technique.
Default and On demand routing - Advance Computer NetworksSonali Parab
Routing is the process of selecting best paths in a network. In the past, the term routing was also used to mean forwarding network traffic among networks. However this latter function is much better described as simply forwarding. Routing is performed for many kinds of networks, including the telephone network (circuit switching), electronic data networks (such as the Internet), and transportation networks.
In packet switching networks, routing directs packet forwarding (the transit of logically addressed network packets from their source toward their ultimate destination) through intermediate nodes. Intermediate nodes are typically network hardware devices such as routers, bridges, gateways, firewalls, or switches. General-purpose computers can also forward packets and perform routing, though they are not specialized hardware and may suffer from limited performance. The routing process usually directs forwarding on the basis of routing tables which maintain a record of the routes to various network destinations. Thus, constructing routing tables, which are held in the router's memory, is very important for efficient routing. Most routing algorithms use only one network path at a time. Multipath routing techniques enable the use of multiple alternative paths.
Comparison of different MANET routing protocols in wireless ADHOCAmitoj Kaur
In this project, AODV and Flooding routing protocols using different parameter metrics have been simulated and analyzed
Simulation results show that performance parameters of the routing protocols may vary depending on network load, mobility and network size.
Under G-Sense Model, AODV experience the highest Packet Delivery Fraction and Throughput with the increase of nodes stop time, and mobile nodes number.
AODV and Simple Flooding performance is due to their on demand characteristics to determine the freshness of the route. And it is proved also that AODV has a slightly higher Average end-to-end Delay than Simple Flooding.
Comparative Analysis of MANET Routing Protocols and Cluster Head Selection Te...IJERA Editor
Mobile Ad-hoc Network is a kind of wireless network. It is a backbone of new generation advanced communication technology. MANET is an ideal applicant for rescue and emergency situation due to its independence of connected devices of fixed wires. This paper represents a work on trust based system in MANET cluster that can be used to improve the performance of the network even in the existence of not trusted nodes. In the cluster architecture, cluster head and gateway nodes form a communication for routing among neighbouring clusters. But selection of cluster head is the important problem in dynamic Ad-hoc network because cluster head work as coordinator in clustered architecture. In this work, some values have used correspond to the threshold values of forward packet and dropped packet of each node within the network cluster. These values have been used dynamically updated every time and the node is selected as cluster head. In this technique of selecting the node as cluster head, the node which has maximum trusted value is elected as cluster head and this information is updated in every node’s trusted table. After implementation of our desired work, the proposed Dynamic Trust Evaluation of Cluster Head (DTE-CH) technique is analysed with traditional routing protocols and traditional clustering technique viz. Highest Degree Algorithm. The simulation is done by using network simulator software on the basis of different performance metrics throughput, packet delivery ratio, routing overhead, packet drop, average end to end delay and remain energy. Simulation result presents that proposed DTE-CH technique improves the performance of network as compare to most suitable existing AODV MANET protocol based technique as well as traditional highest degree clustering technique.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
1. 1
Module: Internet of Things
Lecture 4: Network
Dr Payam Barnaghi, Dr Chuan H Foh
Centre for Communication Systems Research
Electronic Engineering Department
University of Surrey
Autumn Semester 2015
4. Network Module
RF-based IoT applications
− Communication module only provides data link
solution
− i.e. transmitting a packet between nodes within the
radio range
− Network module is needed to provide a solution
for end-to-end packet delivery
− Since source/destination pair may not be within each
other radio range, intermediate nodes are needed to
forward packet
− It is a distributed system. All nodes need to perform
networking related tasks.
− It is often software implementation.
4
5. Network Module
− RF-based IoT applications: Multi-hop Wireless
Network. Some examples:
− Wireless Sensor Networks (WSNs)
− Mobile Wireless Ad hoc Networks (MANETs)
− Wireless Mesh Networks (WMNs)
− Vehicular Ad Hoc Networks (VANETs)
− and others...
− Main concern: Reliability & Performance
5
6. Network Module: Roles
− Management:
− Packet: Adapting the packet sizes and formats
− Address: Adapting and/or resolving addresses
− Device: Joining/leaving of nodes
− Service: Providing adds-on services such as security
− Operational:
− Route discovery & maintenance
− Packet forwarding
6
8. Common Routing Techniques
− Flooding
− When receiving a packet, each node rebroadcasts the
packet
− No memory is kept in a node
− Very wasteful in bandwidth usage
− Source Routing
− A source node partially or completely specifies the route
that a packet should be forwarded
− Source node is responsible for finding the route to the
destination
− Implementation: DSR
8
9. Common Routing Techniques
− Distance Vector
− Exchange distance vectors only with neighbours to
establish routing tables
− Less traffic for table maintenance makes it suitable for
wireless networks
− Implementation: RIP, AODV, etc
− Link State
− Flood link information in the network and use Dijkstra’s
algorithm to compute routing tables
− Popular solution in wired network. Not adequate for
wireless, as it requires network-wide flooding
− Implementation: OSPF, OLSR, etc
9
10. Common Routing Techniques
− Path Vector
− Based on distance vector, path information is used
instead of distance
− Permit implementation of some policy to take control of
the route
− Used in inter-domain routing
− Implementation: BGP
10
11. Route Establishment & Maintenance
− Proactive (table-driven):
− Nodes maintain a table describing how a packet should
be forwarded to destinations
− It is more suitable for networks with static topology
− Reactive (on-demand):
− Upon a request, nodes flood the network to find the
destination
− It is more suitable for networks with changing topology
− Mixed:
− Hybrid: Operate both proactive and reactive routing
− Hierarchical: Separate nodes into different levels and
use different routing techniques in different levels 11
12. Routing in IoT
− Ad hoc On-demand Distance Vector (AODV)
− Specified in RFC 3561
− Implemented in ZigBee
− IPv6 Routing Protocol for Low-Power and Lossy
Networks (RPL)
− Specified in RFC 6550
− Implemented in ContikiOS, TinyOS
12
NOTE: We’ll also review Flooding & Source Routing
13. Flooding
− When receiving a packet
− If it is not seen before, broadcast the packet
− Else discard the packet
13
A
B D
H
C
G
E
Source
Destination
Broadcast
the packet
Destination
first received
the packet
from D
(ABDF)
F
14. Source Routing
− In source routing, the source takes control of the
forwarding
− Basic idea:
− The SOURCE broadcasts a REQUEST
− Each node include the path information in the REQUEST
− When the REQUEST reaches the DESTINATION, the
DESTINATION unicasts a REPLY with the path info
− When the REPLY reaches the SOURCE, it may transmit data
packet with the received path info included in the header
− Each intermediate node uses the path info in the header to
forward the data packets
− Each node maintains route cache to improve route
discovery performance
14
15. Source Routing: Example
− RREQ: Route Request
− RREP: Route Reply
15
A
B D
H
C
G
E
RREQ
Source
Destination
A
F
A-B A-B-D
A-B-D-G
A-B-D
A
A-C
A-B
RREP
A-B-D-H
A-B-D-H
A-B-D-H
16. 16
Distance Vector
8 12
10 6
A B D
C
E F G H
I J L
K
A B C D E F G H I J K L
A 0 12 25 40 14 23 18 17 21 8 24 29
I 24 36 18 27 7 20 31 20 0 10 22 33
H 20 31 19 8 30 19 6 0 14 12 22 9
K 21 28 36 24 22 40 31 19 22 6 0 9
The distance vector published by A, I, H, K to J:
A B C D E F G H I J K L
J 8 20 28 20 17 30 18 12 10 0 6 15
via A A I H I I H H I --- K K
J’s new distance vector and routing table:
Node J has been switched on
10+18
8+25
6+36
(source, distance, next hop)
C 28 I
17. AODV
− Ad hoc On-demand Distance Vector (AODV)
− Reactive Routing using Distance Vector
− Basic idea:
− Activity starts when there is a demand for transmission
− The SOURCE broadcasts a REQUEST
− Each node rebroadcasts the REQUEST creates DISTANCE
VECTOR for the reverse path
− When the REQUEST reaches the DESTINATION, the
DESTINATION unicasts a REPLY
− Each participated node forwards the REPLY creates
DISTANCE VECTOR for the forward path
− When the REPLY reaches the SOURCE, data transmission
may start
17
18. AODV: RREQ
− Route Request (RREQ) broadcasting
− The source broadcasts a RREQ to find a connection
− Intermediate nodes rebroadcast the RREQ to others
− While rebroadcasting, intermediate nodes create a
temporary route information recording the reverse path
(i.e. source, number of hops, next hop)
18
A
B D
H
C
G
E
RREQ
Source
Destination
To A, 1 hop, via A
F
19. AODV: RREP
− Returning of Route Reply (RREP)
− Once RREQ reaches the destination, the destination
unicasts RREP to its “next hop”
− Each participated node forwards RREP to its “next hop” and
record the forward path
− Once the RREP reaches the source, the source can transmit
its data packets to its “next hop”
A
B D
H
C
G
E
RREQ
Source
Destination
To A, 1 hop, via A
F
RREP
To H, 2 hops, via D
19
20. AODV: Some management issues
− Distance Vector maintenance
− A reverse path is purged after a timeout interval (to
make sure the interval is long enough for RREP
unicasting to complete)
− A forward path is purged after it is not used for some
time
− Enhancements
− Intermediate nodes with information to the destination
can reply RREP
− Add sequence numbers to packets to avoid duplicate
rebroadcasting
− Use “time to live” to limit the rebroadcasting of RREQ
20
21. IPv6 Routing Protocol for Low-Power
and Lossy Networks (RPL)
− Background:
− Need for Low power and Lossy Networks (LLN)
− IETF formed a Working Group called Routing Over Low
power and Lossy Networks (ROLL) in 2008
− ROLL developed “Ripple” routing protocol (RPL)
− RPL is a Distance Vector IPv6 routing protocol for
LLNs
− RPL is a proactive routing protocol (periodic
activity to construct route)
− RPL permits multiple routes (or graphs), each
with some specific objective
21
22. RPL
− PRL is about building a Destination Oriented
Directed Acyclic Graph (DODAG) with some
objectives
− Destination Oriented, single destination with a root
− Directed Acyclic Graph, no loop
− DODAG building process
− A node is designated as a root
− A set of new ICMPv6 control messages is created
− DIS: DODAG Information Solicitation
− DIO: DODAG Information Object
− DAO: DODAG Destination Advertisement Object
− An Objective Function (OF) is specified for each node to
compute its rank in the graph
− see also RFC 6551 “Routing Metrics Used for Path
Calculation in Low-Power and Lossy Networks” 22
23. RPL: DODAG Building Process
− Procedure:
− The root starts broadcasting DIO
− Upon receiving DIO, each node
− computes its rank based on the OF
− chooses a neighbour with a rank lower than itself as
preferred parent
− broadcasts DIO message
23
A
B D
H
C
G
E
Root
F
DIO
DIO
Preferred parent
24. RPL: DODAG Building Process
− Assuming shortest path is used as the objective
function (OF), B will choose A as its preferred
parent.
24
A
B D
H
C
G
E
Root
F
Preferred parent
B receives a 2nd DIO
message discards it
(based on the OF)
C broadcasts
DIO
25. RPL: DODAG Building Process
− B broadcasts DIO, other nodes rebroadcast DIO
and set their preferred parent based on the
objective function.
25
A
B D
H
C
G
E
Root
F
Preferred parent
DIO
B broadcasts DIO
26. RPL: DODAG Building Process
− Procedure:
− The broadcasting of DIO continues until all nodes have
seen the DIO
− By now, each node should have nominated one of its
neighbours to be its preferred parent
− A tree is built for UPWARD routing (or MP2P traffic)
26
A
B D
H
C
G
E
Root
F
Preferred parent
27. RPL: P2MP P2P
− Point-to-Multi-Point (P2MP) for Downward traffic
− Each node transmits a DAO message to the root
− Each intermediate node appends its ID and relays DAO
to the root
− Each node can make use of the passing DAO messages
to build a subtree for downward traffic
− This type of node is called a storing node
− A node without this storing capability is called a non-
storing node
− The root will build and store a complete tree for
downward traffic
− Downward traffic can be routed using source routing
− Point-to-Point (P2P) traffic
− P2P is done by upward+downward transmissions
27
28. RPL: Topology Maintenance
− Topology maintenance
− A Trickle timer to control the sending rate of DIO (see
also RFC 6206 “The Trickle Algorithm”)
− Trickle's basic primitive is simple: every so often, a node
transmits data unless it hears a few other transmissions
whose data suggest its own transmission is redundant
− When routing inconsistencies are detected (e.g. loops,
loss of a parent, etc), Trickle timer is reset to the
minimum value to get the problems fixed quickly
28
29. Mesh-under versus Route-over
− Relaying of packets can be performed at Layer 2
(mesh-under) or layer 3 (route-over)
− Layer-2 packet switching
− It creates a single layer-2 domain, all nodes appear to
be directly connected to each other somehow
− It may offer simpler solution
− It may offer lower transmission delay
− Layer-3 packet routing
− It separates data link and routing operations
− It may offer better management of a large network
29
31. Network Performance
− Power Supply:
− limited power supply
− Power Consumption:
− Power consumption of communications is relatively high
− Network establishment and maintenance need
communications
− Departure of some nodes may cause the network to fail
partially or totally (e.g. nodes connecting to the
gateway, nodes connecting two islands of networks, etc)
31
32. Performance:
− Deployment of nodes:
− Bottleneck: When all flows aggregate at a particular
node, the node may represent the bottleneck of the
network
− Possible solutions: add more nodes to create other
paths; add gateways to divert traffic flows
32
This node needs to
forward packet for a large
group of nodes
When all nodes transmit a packet,
this node needs to transmit its
packet and relay 7 others!
33. Performance:
− Deployment of nodes:
− Network lifetime: Nodes nearer to the gateway perform
more packet forwarding tasks. Their departures (due to
flat battery) may cause the network to fail.
− Possible solutions: add more nodes around the gateway;
use higher capacity battery
33
When this node fails, a group
of nodes will be disconnected
from the gateway
34. Performance:
− Position of a gateway:
− Bottleneck: Gateway may become bottleneck of traffic
flows if not adequately positioned in the network
− Possible solutions: reposition the gateway or nodes
around it and/or add more gateways to ease the
congestion
34
Bottleneck occurs at the
around the gateway
35. Performance:
− Position of a gateway:
− Delay: Nodes far away from the gateway may result in
long end-to-end transmission delay
− Possible solutions: relocating the gateway and/or place
more gateways. Ideally, we should keep the number of
hops between a node and the gateway as low as
possible
35
Some packets need 6 hops to
reach the gateway!
36. Summary
− Understand the roles and functions of network
module
− Understand various routing technologies related
to IoT applications
− Understand the impact of nodes/gateway
deployment on network performance
36