Content Caching and Scheduling in Wireless Networks
With Elastic and Inelastic Traffic
ABSTRACT:
The rapid growth
of wireless content access implies the need for content placement and
scheduling at wireless base stations. We study a system under which users are
divided into clusters based on their channel conditions, and their requests are
represented by different queues at logical front ends. Requests might be
elastic (implying no hard delay constraint) or inelastic (requiring that a
delay target be met). Correspondingly, we have request queues that indicate the
number of elastic requests, and deficit queues that indicate the deficit in
inelastic service. Caches are of finite size and can be refreshed periodically
from a media vault. We consider two cost models that correspond to inelastic
requests for streaming stored content and real-time streaming of events,
respectively. We design provably optimal policies that stabilize the request
queues (hence ensuring finite delays) and reduce average deficit to zero [hence
ensuring that the quality-of-service (QoS) target is met at small cost. We
illustrate our approach through simulations.
EXISTING SYSTEM:
The past few
years have seen the rise of smart handheld wireless devices as a means of
content consumption. Content might include streaming applications in which
chunks of the file must be received under hard delay constraints, as well as
file downloads such as software updates that do not have such hard constraints.
The core of the Internet is well provisioned, and network capacity constraints
for content delivery are at the media vault (where content originates) and at
the wireless access links at end-users. Hence, a natural location to place
caches for a content distribution network (CDN) would be at the wireless
gateway, which could be a cellular base station through which users obtain
network access. Furthermore, it is natural to try to take advantage of the
inherent broadcast nature of the wireless medium to satisfy multiple users
simultaneously. There are multiple cellular base stations (BSs), each of which
has a cache in which to store content. The content of the caches can be
periodically refreshed through accessing a media vault. We divide users into
different clusters, with the idea that all users in each cluster are
geographically close such that they have statistically similar channel
conditions and are able to access the same base stations. Note that multiple
clusters could be present in the same cell based on the dissimilarity of their
channel conditions to different base stations. The requests made by each
cluster are aggregated at a logical entity that we call a front end (FE)
associated with that cluster.
DISADVANTAGES
OF EXISTING SYSTEM:
·
The
wireless network between the caches to the users has finite capacity.
·
Refreshing content in the caches from the
media vault incurs a cost.
PROPOSED SYSTEM:
In this paper,
we develop algorithms for content distribution with elastic and inelastic
requests. We use a request queue to implicitly determine the popularity of
elastic content. Similarly,the deficit queue determines the necessary service
for inelastic requests. Content may be refreshed periodically at caches. We
study two different kinds of cost models, each of which is appropriate for a
different content distribution scenario. The first is the case of file
distribution (elastic) along with streaming of stored content (inelastic),
where we model cost in terms of the frequency with which caches are refreshed.
The second is the case of streaming of content that is generated in real-time,
where content expires after a certain time, and the cost of placement of each
packet in the cache is considered.
ADVANTAGES
OF PROPOSED SYSTEM:
·
It
stabilizes the system load within the
capacity region.
·
Minimizes
the average expected cost while stabilizing the deficit queues
SYSTEM
REQUIREMENTS:
HARDWARE REQUIREMENTS:
Ø
System : Pentium IV 2.4 GHz.
Ø
Hard Disk :
40 GB.
Ø
Floppy Drive : 1.44
Mb.
Ø
Monitor : 15
VGA Colour.
Ø
Mouse :
Logitech.
Ø Ram : 512 Mb.
SOFTWARE
REQUIREMENTS:
Ø Operating system : Windows
XP/7.
Ø Coding Language : ASP.net,
C#.net
Ø Tool : Visual Studio 2010
Ø Database : SQL
SERVER 2008
REFERENCE:
Navid Abedini
and Srinivas Shakkottai “Content
Caching and Scheduling in Wireless Networks With Elastic and Inelastic Traffic”
IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 22, NO. 3, JUNE 2014.
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