SlideShare a Scribd company logo
Resource Allocation for QoS Support in Wireless Mesh
Networks
ABSTRACT:
Many next generation applications (such as video flows) are likely to have
associated minimum data rate requirements in order to ensure satisfactory quality
as perceived by end-users. In this paper, we develop a framework to address the
problem of maximizing the aggregate utility of traffic flows in a multi-hop wireless
network, with constraints imposed both due to self-interference and minimum rate
requirements. The parameters that are tuned in order to maximize the utility are (i)
transmission powers of individual nodes and (ii) the channels assigned to the
different communication links. Our framework is based on using across-
decomposition technique that takes both inter-flow interference and self-
interference into account. The output of our framework is a schedule that dictates
what links are to be activated in each slot and the parameters associated with each
of those links. If the minimum rate constraint cannot be satisfied for all of the
flows, the framework intelligently rejects a sub-set of the flows and recomputes a
schedule for the remaining flows. We also design an admission control module that
determines if new flows can be admitted without violating the rate requirements of
the existing flows in the network. We provide numerical results to demonstrate the
efficacy of our framework.
EXISTING SYSTEM:
The problem of resource allocation and congestion control in wired networks has
received a lot of attention. In their seminal work, Kelly et al. have modeled the
problem of flow control as an optimization problem where the objective is to
maximize the aggregate utility of elastic traffic sources subject to capacity
constraints on the links that compose the network. Inspired by Kelly’s work, there
has been follow up work, where TCP congestion control is modeled a convex
optimization problem, the objective being the maximization of an aggregate user
utility; in these efforts distributed primaldual solutions to the problem are
proposed.
DISADVANTAGES OF EXISTING SYSTEM:
In contrast with wireline networks, the capacity of a wireless link is not dependent
on other flows in the network but on other flows that use links on the same channel
(and that are close enough) and external interference. The dependencies between
flows is regulated by the protocols at both the link and transport layers. However,
these prior efforts do not consider the provision of quality-of-service in terms of
supporting minimum rates to the flows that share the network. More importantly,
the QoS needs to be provided under conditions of self-interference, where the
packets of a flow interfere with other packets that belong to the same flow along a
multi-hop path.
PROPOSED SYSTEM:
In this paper, we propose a framework for maximizing the aggregate utility of
traffic sources while adhering to the capacity constraints of each link and the
minimum rate requirements imposed by each of the sources. The framework takes
into account the self-interference of flows and assigns (a) channels (b) transmission
power levels and (c) time slots to each link such that the above objective is
achieved. It dictates the rates at which each traffic source will send packets such
that the minimum rate requirements of all coexisting flows are met. If the
minimum rate requirements of all the flows cannot be met, the framework rejects a
subset of flows (based on fairness considerations) and recomputes the schedule and
allocates resources to each of the remaining flows.
ADVANTAGES OF PROPOSED SYSTEM:
 The framework maximizes the aggregate utility of flows taking into account
constraints that arise due to self-interference (wireless channel imposed
constraints) and minimum rate requirements of sources (QoS requirements).
 If a solution is not feasible, the framework selectively drops a few of the
sources and redistributes the resources among the others in a way that their
QoS requirements are met.
 The proposed framework readily leads to a simple and effective admission
control mechanism.
 We demonstrate the efficacy of our approach with numerical results. We
also theoretically compute performance bounds with our network, as
compared with an optimal strategy.
SYSTEM CONFIGURATION:-
HARDWARE REQUIREMENTS:-
 Processor - Pentium –IV
 Speed - 1.1 Ghz
 RAM - 256 MB
 Hard Disk - 20 GB
 Key Board - Standard Windows Keyboard
 Mouse - Two or Three Button Mouse
 Monitor - SVGA
SOFTWARE REQUIREMENTS:
• Operating system : - Windows XP.
• Coding Language : C#.Net.
REFERENCE:
Tae-Suk Kim, Yong Yang, Jennifer C. Hou,Fellow, IEEE,and Srikanth V.
Krishnamurthy,Fellow, IEEE “Resource Allocation for QoS Support in Wireless
Mesh Networks” - IEEE TRANSACTIONS ON WIRELESS
COMMUNICATIONS, 2013

More Related Content

PDF
On availability performability tradeoff in wireless mesh networks
PDF
Paper id 24201445
DOCX
secured communication over wireless broadcast networks
DOC
A neighbor coverage based probabilistic rebroadcast for reducing routing over...
PPTX
MANET Experiment - I (Using Network Simulator NetSim -www.tetcos.com)
PPTX
Non concave network utility maximization - A distributed optimization approach
DOCX
Cooperative load balancing and dynamic
PDF
Cooperative load balancing and dynamic
On availability performability tradeoff in wireless mesh networks
Paper id 24201445
secured communication over wireless broadcast networks
A neighbor coverage based probabilistic rebroadcast for reducing routing over...
MANET Experiment - I (Using Network Simulator NetSim -www.tetcos.com)
Non concave network utility maximization - A distributed optimization approach
Cooperative load balancing and dynamic
Cooperative load balancing and dynamic

What's hot (19)

PDF
Cooperative load balancing and dynamic channel allocation for cluster based m...
DOC
Stochastic bandwidth estimation in networks with random service
PDF
Efficient Load Balancing Routing in Wireless Mesh Networks
PPTX
Cooperative load balancing and dynamic channel allocation for cluster based m...
PDF
Regressive admission control enabled by real time qos measurements
DOCX
IEEE 2014 NS2 NETWORKING PROJECTS Temporal traffic dynamics improve the conn...
PDF
Congestion Control in Wireless Sensor Networks- An overview of Current Trends
PDF
Multi hop distributed coordination in
DOCX
Power controlled medium access control
PDF
Analysis of Link State Resource Reservation Protocol for Congestion Managemen...
PDF
Reduce Handover Delay Using the HSBCC Based Buffer Over Flow In Wimax Network
PPT
Multipath Routing
PDF
PERFORMANCE ANALYSIS OF WIRELESS MESH NETWORK USING ADAPTIVE INFORMANT FACTOR...
PPTX
band width ppt
DOCX
Cooperative load balancing and dynamic channel allocation for cluster based m...
PDF
Experimental evaluation of scalability and reliability of a feedback based up...
PDF
CONVEX OPTIMIZATION BASED CONGESTION CONTROL IN LAYERED SATELLITE NETWORKS
DOCX
Delay based network utility maximization
PDF
An automated dynamic offset for network selection in heterogeneous networks
Cooperative load balancing and dynamic channel allocation for cluster based m...
Stochastic bandwidth estimation in networks with random service
Efficient Load Balancing Routing in Wireless Mesh Networks
Cooperative load balancing and dynamic channel allocation for cluster based m...
Regressive admission control enabled by real time qos measurements
IEEE 2014 NS2 NETWORKING PROJECTS Temporal traffic dynamics improve the conn...
Congestion Control in Wireless Sensor Networks- An overview of Current Trends
Multi hop distributed coordination in
Power controlled medium access control
Analysis of Link State Resource Reservation Protocol for Congestion Managemen...
Reduce Handover Delay Using the HSBCC Based Buffer Over Flow In Wimax Network
Multipath Routing
PERFORMANCE ANALYSIS OF WIRELESS MESH NETWORK USING ADAPTIVE INFORMANT FACTOR...
band width ppt
Cooperative load balancing and dynamic channel allocation for cluster based m...
Experimental evaluation of scalability and reliability of a feedback based up...
CONVEX OPTIMIZATION BASED CONGESTION CONTROL IN LAYERED SATELLITE NETWORKS
Delay based network utility maximization
An automated dynamic offset for network selection in heterogeneous networks
Ad

Similar to Resource allocation for qo s support in wireless mesh networks (20)

PDF
IEEE 2015 NS2 Projects
PDF
IEEE 2015 NS2 Projects
PDF
D1102031727
PDF
Modified PREQ in HWMP for Congestion Avoidance in Wireless Mesh Network
DOCX
cost effective resource allocation of overlay routing relay nodes
DOCX
Final Year IEEE Project Titles 2015
DOCX
Final Year Project IEEE 2015
PDF
A novel routing technique for mobile ad hoc networks (manet)
PDF
Dynamic Traffic Management Services to Provide High Performance in IntelRate ...
PDF
Enhancement of qos in multihop wireless networks by delivering cbr using lb a...
PDF
Enhancement of qos in multihop wireless networks by delivering cbr using lb a...
PDF
Dynamic Traffic Management Services to Provide High Performance in IntelRate ...
PDF
A way of managing data center networks
PDF
Call Admission Control Scheme With Multimedia Scheduling Service in WiMAX Net...
DOC
8.conclusion
PDF
Traffic-aware adaptive server load balancing for softwaredefined networks
PDF
Iisrt komathi krishna (networks)
PDF
Analysis of Rate Based Congestion Control Algorithms in Wireless Technologies
DOCX
JPJ1433 Cost-Effective Resource Allocation of Overlay Routing Relay Nodes
DOC
Bandwidth estimation for ieee 802
IEEE 2015 NS2 Projects
IEEE 2015 NS2 Projects
D1102031727
Modified PREQ in HWMP for Congestion Avoidance in Wireless Mesh Network
cost effective resource allocation of overlay routing relay nodes
Final Year IEEE Project Titles 2015
Final Year Project IEEE 2015
A novel routing technique for mobile ad hoc networks (manet)
Dynamic Traffic Management Services to Provide High Performance in IntelRate ...
Enhancement of qos in multihop wireless networks by delivering cbr using lb a...
Enhancement of qos in multihop wireless networks by delivering cbr using lb a...
Dynamic Traffic Management Services to Provide High Performance in IntelRate ...
A way of managing data center networks
Call Admission Control Scheme With Multimedia Scheduling Service in WiMAX Net...
8.conclusion
Traffic-aware adaptive server load balancing for softwaredefined networks
Iisrt komathi krishna (networks)
Analysis of Rate Based Congestion Control Algorithms in Wireless Technologies
JPJ1433 Cost-Effective Resource Allocation of Overlay Routing Relay Nodes
Bandwidth estimation for ieee 802
Ad

Recently uploaded (20)

PDF
Microbial disease of the cardiovascular and lymphatic systems
PPTX
GDM (1) (1).pptx small presentation for students
PPTX
human mycosis Human fungal infections are called human mycosis..pptx
PPTX
PPH.pptx obstetrics and gynecology in nursing
PDF
Sports Quiz easy sports quiz sports quiz
PPTX
school management -TNTEU- B.Ed., Semester II Unit 1.pptx
PDF
Computing-Curriculum for Schools in Ghana
PDF
102 student loan defaulters named and shamed – Is someone you know on the list?
PDF
The Lost Whites of Pakistan by Jahanzaib Mughal.pdf
PDF
grade 11-chemistry_fetena_net_5883.pdf teacher guide for all student
PDF
BÀI TẬP BỔ TRỢ 4 KỸ NĂNG TIẾNG ANH 9 GLOBAL SUCCESS - CẢ NĂM - BÁM SÁT FORM Đ...
PDF
Saundersa Comprehensive Review for the NCLEX-RN Examination.pdf
PDF
Anesthesia in Laparoscopic Surgery in India
PPTX
IMMUNITY IMMUNITY refers to protection against infection, and the immune syst...
PDF
STATICS OF THE RIGID BODIES Hibbelers.pdf
PDF
Pre independence Education in Inndia.pdf
PPTX
Cell Types and Its function , kingdom of life
PDF
TR - Agricultural Crops Production NC III.pdf
PDF
Chapter 2 Heredity, Prenatal Development, and Birth.pdf
PPTX
Pharma ospi slides which help in ospi learning
Microbial disease of the cardiovascular and lymphatic systems
GDM (1) (1).pptx small presentation for students
human mycosis Human fungal infections are called human mycosis..pptx
PPH.pptx obstetrics and gynecology in nursing
Sports Quiz easy sports quiz sports quiz
school management -TNTEU- B.Ed., Semester II Unit 1.pptx
Computing-Curriculum for Schools in Ghana
102 student loan defaulters named and shamed – Is someone you know on the list?
The Lost Whites of Pakistan by Jahanzaib Mughal.pdf
grade 11-chemistry_fetena_net_5883.pdf teacher guide for all student
BÀI TẬP BỔ TRỢ 4 KỸ NĂNG TIẾNG ANH 9 GLOBAL SUCCESS - CẢ NĂM - BÁM SÁT FORM Đ...
Saundersa Comprehensive Review for the NCLEX-RN Examination.pdf
Anesthesia in Laparoscopic Surgery in India
IMMUNITY IMMUNITY refers to protection against infection, and the immune syst...
STATICS OF THE RIGID BODIES Hibbelers.pdf
Pre independence Education in Inndia.pdf
Cell Types and Its function , kingdom of life
TR - Agricultural Crops Production NC III.pdf
Chapter 2 Heredity, Prenatal Development, and Birth.pdf
Pharma ospi slides which help in ospi learning

Resource allocation for qo s support in wireless mesh networks

  • 1. Resource Allocation for QoS Support in Wireless Mesh Networks ABSTRACT: Many next generation applications (such as video flows) are likely to have associated minimum data rate requirements in order to ensure satisfactory quality as perceived by end-users. In this paper, we develop a framework to address the problem of maximizing the aggregate utility of traffic flows in a multi-hop wireless network, with constraints imposed both due to self-interference and minimum rate requirements. The parameters that are tuned in order to maximize the utility are (i) transmission powers of individual nodes and (ii) the channels assigned to the different communication links. Our framework is based on using across- decomposition technique that takes both inter-flow interference and self- interference into account. The output of our framework is a schedule that dictates what links are to be activated in each slot and the parameters associated with each of those links. If the minimum rate constraint cannot be satisfied for all of the flows, the framework intelligently rejects a sub-set of the flows and recomputes a schedule for the remaining flows. We also design an admission control module that determines if new flows can be admitted without violating the rate requirements of
  • 2. the existing flows in the network. We provide numerical results to demonstrate the efficacy of our framework. EXISTING SYSTEM: The problem of resource allocation and congestion control in wired networks has received a lot of attention. In their seminal work, Kelly et al. have modeled the problem of flow control as an optimization problem where the objective is to maximize the aggregate utility of elastic traffic sources subject to capacity constraints on the links that compose the network. Inspired by Kelly’s work, there has been follow up work, where TCP congestion control is modeled a convex optimization problem, the objective being the maximization of an aggregate user utility; in these efforts distributed primaldual solutions to the problem are proposed. DISADVANTAGES OF EXISTING SYSTEM: In contrast with wireline networks, the capacity of a wireless link is not dependent on other flows in the network but on other flows that use links on the same channel (and that are close enough) and external interference. The dependencies between flows is regulated by the protocols at both the link and transport layers. However, these prior efforts do not consider the provision of quality-of-service in terms of supporting minimum rates to the flows that share the network. More importantly,
  • 3. the QoS needs to be provided under conditions of self-interference, where the packets of a flow interfere with other packets that belong to the same flow along a multi-hop path. PROPOSED SYSTEM: In this paper, we propose a framework for maximizing the aggregate utility of traffic sources while adhering to the capacity constraints of each link and the minimum rate requirements imposed by each of the sources. The framework takes into account the self-interference of flows and assigns (a) channels (b) transmission power levels and (c) time slots to each link such that the above objective is achieved. It dictates the rates at which each traffic source will send packets such that the minimum rate requirements of all coexisting flows are met. If the minimum rate requirements of all the flows cannot be met, the framework rejects a subset of flows (based on fairness considerations) and recomputes the schedule and allocates resources to each of the remaining flows. ADVANTAGES OF PROPOSED SYSTEM:  The framework maximizes the aggregate utility of flows taking into account constraints that arise due to self-interference (wireless channel imposed constraints) and minimum rate requirements of sources (QoS requirements).
  • 4.  If a solution is not feasible, the framework selectively drops a few of the sources and redistributes the resources among the others in a way that their QoS requirements are met.  The proposed framework readily leads to a simple and effective admission control mechanism.  We demonstrate the efficacy of our approach with numerical results. We also theoretically compute performance bounds with our network, as compared with an optimal strategy. SYSTEM CONFIGURATION:- HARDWARE REQUIREMENTS:-  Processor - Pentium –IV  Speed - 1.1 Ghz  RAM - 256 MB  Hard Disk - 20 GB  Key Board - Standard Windows Keyboard  Mouse - Two or Three Button Mouse
  • 5.  Monitor - SVGA SOFTWARE REQUIREMENTS: • Operating system : - Windows XP. • Coding Language : C#.Net. REFERENCE: Tae-Suk Kim, Yong Yang, Jennifer C. Hou,Fellow, IEEE,and Srikanth V. Krishnamurthy,Fellow, IEEE “Resource Allocation for QoS Support in Wireless Mesh Networks” - IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2013