New User Special Price Expires in

Let's log you in.

Sign in with Facebook


Don't have a StudySoup account? Create one here!


Create a StudySoup account

Be part of our community, it's free to join!

Sign up with Facebook


Create your account
By creating an account you agree to StudySoup's terms and conditions and privacy policy

Already have a StudySoup account? Login here

Advanced Distributed Computing

by: Lowell Harris

Advanced Distributed Computing COSC 7388

Marketplace > University of Houston > Chemistry > COSC 7388 > Advanced Distributed Computing
Lowell Harris
GPA 3.94

Rong Zheng

Almost Ready


These notes were just uploaded, and will be ready to view shortly.

Purchase these notes here, or revisit this page.

Either way, we'll remind you when they're ready :)

Preview These Notes for FREE

Get a free preview of these Notes, just enter your email below.

Unlock Preview
Unlock Preview

Preview these materials now for free

Why put in your email? Get access to more of this material and other relevant free materials for your school

View Preview

About this Document

Rong Zheng
Class Notes
25 ?




Popular in Course

Popular in Chemistry

This 10 page Class Notes was uploaded by Lowell Harris on Saturday September 19, 2015. The Class Notes belongs to COSC 7388 at University of Houston taught by Rong Zheng in Fall. Since its upload, it has received 66 views. For similar materials see /class/208163/cosc-7388-university-of-houston in Chemistry at University of Houston.


Reviews for Advanced Distributed Computing


Report this Material


What is Karma?


Karma is the currency of StudySoup.

You can buy or earn more Karma at anytime and redeem it for class notes, study guides, flashcards, and more!

Date Created: 09/19/15
2232009 Resource Management in Computer Networks Mapping from engineering problems to th t39 lf t Rong Zheng COSC 7388 Two Types of Realworld Problems Make something work a Eg build a car on 4wheel write a compiler Make something work better a What is better Performance profit faster more Resource lesser Management configuration cost lesser 39zi usmm39clu39s Nisanm Niammsksrm HOMERSAPIEN 22 32009 Make things better 0 Problem 1 u Maximize performance subject to resource constraints 0 Problem 2 u Minimize resource usage subject to performance requirements From Engineering Problem Domain specit39ic problem Peri Constrained or unconstrained problem Objective tormulation Constraint formulation Solvable by mg techniques 2232009 A Canonical Formulation maximize fXy st GXy 2 O What makes the problem difficult Objective functions can be quite sophisticated multiple local optimums Extreme points due to constraints Your optimization arsenal Linear programming LP 39 Em Simmons Nonlinearprogramming D slm lex u Duality theory NLP u Decomposition D Convex programming a Branch and bound 39 NLP Duality theory Heuristic solutions a Simulatedannealing a Genetic programming a Swarm intelligence u Tabu search Integer programming D LP VS NLP Mixed integer programming a Generally NPhard From Engineering Problem Domain specific problem Constrained or unconstrained problem Objective tormnlation Constraint formulation Solvable by mm a c l 5 techniques 22 32009 2232009 Objectives for resource sharing 395 x 1 i 1 x o It is often not enough to just i maximize the utilization of the resource n Starvation may arise Certain fairness shall be maintained a How fair is fair Fairness in network protocols CSMA protocols such as 80211 makes each node to have equal access probability in idleness on average a Backoff time 0 CW a Is it really fair If so in what sense If not why Transport control protocol TCP regulates the ow rate based on receiver buffer and network congestion U AIMD 1 n Throu h ut g p m a Is it really fair If so in what sense If not why Many forms of fairness exist Massoulie L Roberts J Bandwidth sharing objectives and algorithms IEEEACM Transactions on Networking Volume 10 Issue 3 Jun 2002 Pages32o 328 Consider the problem of bandwidth sharing Fairness L ows Xi is the rate ofthe ith ow i 1 L Adaxnnunithroughput maxi e Lquoti u Starvation may occur v Maxmin fairness maxmini E L7ti u Optimize for the worse case v Proportional fairness maxi E Llog7ti a Let M be the set of optimal rates M represents any other rate vector then 215 LW MW M S 0 22 32009 22 32009 Fairness cont d Potential delay minimization 21 e L1quoti All forms can admit weighted versions to re ect bias More generally we can have 216 LU7 i Where Uo is a concave function Constraints In networks typical types of constraints are a Link capacity constraints I u Flow constraints a Individual power constraints sum power constraints a None negative constraints binary constraints a 22 32009 Link capacity constraint In wireline relatively straightforward 21 e Alfi 5 C1 In wireless harder to characterize a Halfduplex radio a node cannot transmit and receive at the same time u Contention links in the same contention domain a Interference leads lower attainable data rate or higher loss rate Link capacity C is a function of power distance channel interference level etc Contention constraints K Pairwise contention 1 relationship 9 con ict graph V39 n Denote each link by a vertex 4 u A directed edge e i j if linki interferes with linkj u Clique any two nodes are 39 adjacent 9 models pairwise exclusive relationship Routing Consider a routing matrix RF X L n F the number of ows u L the number of links H Rij 1 if ow i routes through link L 0 otherwise B Let A k1 k2 M be the rate vector of all ows u A R is Putting everything together wi reline case Problem statement D A network N E D A set of ows F with known destination and source D Routing matrix R is given D Objective to maximize fair share among all ows route 0 link 1 link 2 link L route 1 if route 2 i Tome L i o Assume each link has unit capacity What is the max throughput share maxmin share proportional fair share 22 32009 Putting everything together wireless case Problem statement a A multihop wireless network N E default link capac yr n A set of ows F with known destination and source a Routing matrix R is given a Objective to maximize proportional fair share among dl oms 22 32009 10


Buy Material

Are you sure you want to buy this material for

25 Karma

Buy Material

BOOM! Enjoy Your Free Notes!

We've added these Notes to your profile, click here to view them now.


You're already Subscribed!

Looks like you've already subscribed to StudySoup, you won't need to purchase another subscription to get this material. To access this material simply click 'View Full Document'

Why people love StudySoup

Bentley McCaw University of Florida

"I was shooting for a perfect 4.0 GPA this semester. Having StudySoup as a study aid was critical to helping me achieve my goal...and I nailed it!"

Janice Dongeun University of Washington

"I used the money I made selling my notes & study guides to pay for spring break in Olympia, Washington...which was Sweet!"

Jim McGreen Ohio University

"Knowing I can count on the Elite Notetaker in my class allows me to focus on what the professor is saying instead of just scribbling notes the whole time and falling behind."


"Their 'Elite Notetakers' are making over $1,200/month in sales by creating high quality content that helps their classmates in a time of need."

Become an Elite Notetaker and start selling your notes online!

Refund Policy


All subscriptions to StudySoup are paid in full at the time of subscribing. To change your credit card information or to cancel your subscription, go to "Edit Settings". All credit card information will be available there. If you should decide to cancel your subscription, it will continue to be valid until the next payment period, as all payments for the current period were made in advance. For special circumstances, please email


StudySoup has more than 1 million course-specific study resources to help students study smarter. If you’re having trouble finding what you’re looking for, our customer support team can help you find what you need! Feel free to contact them here:

Recurring Subscriptions: If you have canceled your recurring subscription on the day of renewal and have not downloaded any documents, you may request a refund by submitting an email to

Satisfaction Guarantee: If you’re not satisfied with your subscription, you can contact us for further help. Contact must be made within 3 business days of your subscription purchase and your refund request will be subject for review.

Please Note: Refunds can never be provided more than 30 days after the initial purchase date regardless of your activity on the site.