efficient multicast delivery for data redundancy minimization

Efficient Multicast Delivery for Data Redundancy Minimization Over Wireless

Data Centers

Amaldev ks S7 cs Roll no 03 Reg no 12140202

CONTENTSI. INTRODUCTIONII. RELATED WORKSIII. SYSTEM MODEL AND PROBLEM FORMULATION

A. SYSTEM MODELB. PROBLEM FORMULATIONC. AN ILLUSTRATIVE EXAMPLE

1) MULTICAST TREE CONSTRUCTION2) MULTICAST TREE MAINTENANCE

IV. THE MULTICAST TREE CONSTRUCTION V. THE MULTICAST TREE MAINTENANCE VI. PERFORMANCE EVALUATION

A. SIMULATION SETUPSB. SIMULATION RESULTS

VII. CONCLUSION VIII. REFERENCES

I. INTRODUCTION

• With the explosive growth of cloud-based services, large-scale

data centers are widely built for housing critical computing

resources to gain significant economic benefits.

• In data center networks, the cloud-based services are mostly

accomplished by group communications with multicast traffic.

• For instance, a web server redirects queries to a set of indexing

servers. Distributed file systems replicate file chunks to a set of

storage nodes.

• For distributed execution engines such as Map Reduce. the

master node assigns tasks to a group of servers for operative

computations. In social networks (e.g., Facebook, Twitter,

etc) .

• Users frequently share their messages, photos and videos with

their friends, and group communications are also needed. In

group communications, a source node has to transmit one copy

of the data to multiple destination nodes.

II. RELATED WORKS • To achieve group communications, multicast is used to transmit

data to a group of destinations. The first standard of IP(Internet

Protocol) multicast is specified in RFC1112. Then the Internet

Group Management Protocol (IGMP) is defined to allow a host to

join and leave a group, and to report its IP multicast group

membership to neighboring multicast routers .

• The tree structure is commonly adopted for multicast to reduce

redundant data transmissions and avoid unnecessary network

resource usage.

• The source-based tree is established by the shortest-path

algorithm, and each sender requires an individual tree to transmit

its multicast data. This implies that the source-based multicast

tree is more suitable for the applications with few senders in a

multicast group.

• The approaches do not take wireless links into account ,and only

reduce the total number of used wired links, as their major

performance metric, without considering different data rates

requested by heterogeneous cloud services.

A. SYSTEM MODEL

B. PROBLEM FORMULATION

C. AN ILLUSTRATIVE EXAMPLE

1) MULTICAST TREE CONSTRUCTION

2) MULTICAST TREE MAINTENANCE

III. SYSTEM MODEL AND PROBLEM FORMULATION

A. SYSTEM MODELIn a data center, several servers are grouped in a rack and each rack is equipped with a switch. The switch is named as the top-of-rack switch which connects to all the servers in the rack.

Top-of-rack switches are generally connected by aggregation switches and/or core switches, depending on their network topology.

The types of data center network topology include hierarchical topology, Fat-tree and BCube. Considering the deployment cost and complexity of wired links, hierarchical topology is commonly used.

Considering the deployment cost and complexity of wired links, hierarchical topology is commonly used. Moreover, many industries mare trying to deploy access points with 60GHz wireless access technologies on top-of-rack switches to augment network capacity and provide fast connectivity.

B. PROBLEM FORMULATION

In this paper, we are interested in the source-based multicast tree

construction and maintenance, comprised of wired and wireless

links in data center networks. The objective is to minimize the total

multi cast data traffic(ie the transmission redundancy).

C. AN ILLUSTRATIVE EXAMPLE




We use a simple example, to describe the multicast tree construction problem in wireless data centers. Consider the wireless data center shown in Fig.on each rack, there is a pair of top-of-rack switch and access point. The data sent from one top-of-rack switch to another should go through two wired links, while a top-of-rack access.

2) MULTICAST TREE MAINTENANCE• The example depicts the multicast tree maintenance

problem, where the same system settings are used as that in the example of the multicast tree construction.

• More over, in this example, we adopt the two multicast trees constructed in the example of multicast tree construction node of rack 5 joins multicast group 1.Then we attempt to maintain the multicast trees such that the node can receive the multicast data.

• This example demonstrates that the tree maintenance problem is important and non trivial in the minimization of the multicast data traffic and has to be carefully addressed.

IV PERFORMANCE EVALUATION

A. SIMULATION SETUPS B. SIMULATION RESULTS

A. SIMULATION SETUPS• In this section, we develop a simulation model based on a

realistic wireless data center topology, where the hierarchical topology is used according to the deployment of Microsoft to evaluate our proposed algorithms.

• In the network architecture, there are 160 top-of-racks, each of which has one wired switch and one 60GHz wireless access point with a directional narrow-beam antenna.

• The real measurement results from Microsoft have indicated that two parallel 60GHz wireless links are interfered with each other when the distance of the two links is smaller than 22 inches.

• . Note that the width of a rack is about 24 inches. By the geometric-based interference model and the deployment of wireless access points, the transmission range of each wireless link and its interference can be accordingly derived, and an example is shown in Fig.

B. SIMULATION RESULTS

• The total multicast data traffic increases when the number of multicast groups increases for the three algorithms.

• More multicast groups increase more multicast data traffic and use more network resources. However, our proposed algorithm can efficiently reduce the total multicast data traffic against steiner tree and shortest path tree.

1) MULTICAST TREE CONSTRUCTION • The impacts of the number of multicast groups

under different group size distributions on the total multicast data traffic.


• Impacts of the number of joining nodes with power-law distribution on the shows the amount of the increased multicast traffic when there are 50 and 250 multicast groups.

• We observe that the amount of the multicast traffic increases as the number of joining nodes increases for Random, EWDCMT and EWTM-J.This result can be expected because more joining nodes imply more traffic requests

CONCLUSION • We have addressed the group communication issue raised in wireless data

center networks. We explored the multicast tree construction and maintenance problems with the coexistence of wired and wireless links.

• The objective of this paper is to minimize the total multicast traffic.• We provedNP-hardness of the target problems. For the tree construction

problem, we proposed a heuristic algorithm to efficiently use wireless transmission links.

• For the tree maintenance problem, a low-complexity solution was developed to adjust the multicast trees when their receivers join/leave. Finally, we conducted a series of simulations to evaluate the performance of our proposed algorithms.

• The simulation results demonstrated that our proposed algorithms are effective for reducing the total multicast traffic. We also observed some useful insights which can be used to the design of multicast tree construction and maintenance for wireless data center networks.

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efficient multicast delivery for data redundancy minimization

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