ABSTRACT:
Advances in wireless technology and mobile computing have provided a major impetus towards
development of mobile Ad-hoc Network. This networks are selforganizing networks
comprised of wireless nodes that co – operate in order to dynamically establish
communication. In this paper we propose
an opportunisticapproach to resource (parking slot, taxi-cab customer,
etc.) dissemination, in which anobject
propagates the resources it carries to encountered objects, and obtains
newresources in exchange. For example ,
an object finds out about available parking spacesfrom other objects. These spaces may either have been vacated by
these encountered objects or these objects have obtained this information from
other previously encountered ones. Thus
the parking space information transitively spreads out across objects
.Similarly, information about an accident or a taxi cab customer is propagated
transitively.The approach can also be
used in dissemination of resources among pedestrians. The target of the design
is to connect different moving devices together, wirelessly in an small
geographical area.
DATA
IN THE ROAD IN INTELLIGENT
TRANSPORTATION SYSTEMS
INTRODUCTION
Consider an urban area with
hundreds of thousands of
vehicles.Drivers and passengers in these vehicles are interested in information
relevant to their trip.For eg, a driver would like his/her vehicle to
continuously display on a map at any time, the available parking spaces around
the current location of the vehicle.Or, the driver may be interested in the
traffic conditions one mile ahead.such information is important for drivers to
optimize their travel, to alieviate
traffic congestions,or to avoid wasteful driving.the challenge in processing
queries in this highly mobile environment with an acceptable delay,overhead and
accuracy.In this paper we explore a new paradigm that is based on peer to peer
communication in mobile computing.
Mobile Computing is a
technology that allows transmission of data, via a computer, without
having to be connected to a fixed physical link.P2P computing
can be simply
defined as the
sharing of computer
resources and services
by direct exchange. The
peer computer can
respond to request
from other peers.
The p2p computing
model offers a
number of compelling advantages to
individual users and
large organizations. P2p can be
use3d to distribute data and in addition the p2p infrastructure allows direct
access and shared spaces and this can enable remote
maintanance capability.
THE SYSTEM
MODEL:
The system consists of fixed stations
and moving objects. Each station senses
resources and continuously announces them by wireless broadcast. Each announcement message, contains the home
and the create-time of the resource. An object is capable of detecting the
objects that are within its transmission range.
We say that two objects encounter each other when their distance is
smaller than the transmission rang. If
two moving objects travel within the transmission range for a period of time,
after the initial exchange only newly arrived resources are exchanged.
EXAMPLES:
In the parking slots example, a sensor in a
parking slot monitors the slot, and, while unoccupied, announces its
availability to the neighboring vehicles.
In
the car accident example, the event may be announced by the sensor that deploys
the air-bag.
RESOURCES AND THEIR RELEVANCE:
Resources may be spatial, temporal, or spatio-temporal
. Spatio – temporal resources generalize the spatial and the temporal
resources. A spatio – temporal resource,
or a resource for short, is a piece of information about an event(e.g. the
availability of a parking space, or a car accident, the speed of a vehicle at a
particular time – point, the availability of a taxi-cab customer at a
particular location). The event is
specific to a certain location that is referred to as the home of the
resource.Each resource has a time duration for which it is valid. This duration is referred to as the valid
duration. For example, the valid
duration of the resource regarding the availability of a parking space is the
time period since the space becomes available until it is occupied.We use
the following function to compute the
relevance of compute the relevance of resource R:
F (R) = .t - .d (, >0)
Where
d is the distance form the home location of R. and
are constants that represent the decay factors of time and distance
respectively. The bigger the ratio ,
the more the relevance is sensitive to time than to distance; conversely, the
relevance is more sensitive to distance than to time.
DISSEMINATION ALGORITHMS:
In this section we describe two
possible opportunistic resource dissemination algorithms.
OPPORTUNISTIC RESOURCE DISSEMINATION:
The resources in memory are ranked according
to their relevance. If the number of
received resources exceeds the allocated memory,less relevant resources must be
shed from memory to accommodate more relevant ones. We assume that a moving object has a fixed
amount of memory allocated to each application (e.g the user allocates 10
entries for relevant parking slots. In
other words, the user wants only 10 parking slots to be saved and displayed)
Two types of
operations may be performed at a moving object O. The first type is resource
acquisition, which is performed when O is within the coverage area of a station
while the station is announcing a resource R. Upon reception of R, if O’s
memory space is not full, R is saved in memory.
If the memory is full, O computes the relevance of R based on the age of
R and on the distance between the current location of O and the home of R.O
also recomputes the relevance for each
stored resource. If the relevance of R
is higher than that of any stored resource, the least relevant one is purged,
and then R is saved otherwise R is discarded.
The second type of operations is
resource exchange, which is performed when O encounters a new object O’,it neither O nor O’ is in the middle of
data exchange with a third vehicle, the resource exchange is performed between
A and B as follws.O and O’ first exchange their resources. Upon receiving new resources, moving object
O computes the relevance for each
received resource and re-evaluates the relevance of its own resources. If all the resources do not fit in the memory
space of O, the least relevant ones are purged. In either resource acquisition
or resource exchange, when O receives a resource R, if O has a resource R in
its memory such that R and R have the same home and the create-time of R is
greater than that of R’ then R’ is replaced by R.
OPPORTUNISTIC RESOURCE DISSEMINATION WITH INVALIDATION (ORDI)
With ORD, a
resource in an object’s memory may become invalid before it is purged out. This invalid resource introduces wrong
information for decision making. For
example, the resource may indicate an available parking space that is actually
already occupied, or it may indicate a cab request that is already
satisfied. Time may be wasted if the
driver uses this resource to make decisions.
In order to reduce the invalid resources, we developed Opportunistic
Resource Dissemination with Invalidation (ORDI).
ORDI works as
follows. At each station, whenever the
valid duration of a resource R ends, the station starts to announce an
invalidation message for R until the beginning of the announcement of the next
resoure. The invalidation message
contains the following three data items:
i
T invalid (R) the time when R becomes invalid (which is also
the time when the invalidation message is created)
ii
T create (R) the
create-time of R
iii
H(R) the home of R. the invalidation message is a special
resource. Its home is H(R) and its
create-time is T invalid (R), and it uses the same relevance function as a
regular resource. We will refer to the
invalidation message as the invalidating resource of R, and refer to R as a
regular resource. The invaliding
resource is acquired and exchanged similarly to a regular resource. The only difference is a follows. When an invalidating resource (T invalid(R),
T create(R), H(R) is received by an object, the object uses T create (R) and
H(R) to search R in its memory. If R is
found, then it is replaced by the invalidating resource.
QUERYING:
Consider queries that find all the resources within a particular
geographic region R. for example, find all the available parking spaces within certain campus, or find
all the cab requests within five blocks of an area. When a moving object receives such a query
from the user, it sends the query to all the objects that may have information
about resources located inside the queried area. It then computes the answer to the query from
the answers that it receives.
Consider problem (i). Observe that
information about the resources in the region R may travel beyond the
region. Thus, the query destination area
P, i.e. the region to which the query is propagated, may be larger than the
queried region R. Consider the following approach to determine the query
destination area. Suppose that from the
analysis of data dissemination, we know that the maximum distance to which a
resource is propagated is bounded by some constant B. Assume that R is a
polygonal area, and D denotes a disk with radius b. Then P is {R
interior of R the Points which are in the “Sweep” of D when its center
moves along the edges of P} .
Now consider problem (ii), i.e. how the
query is disseminated to all the objects in the destination area. One distinguishes among several situations,
depending on what each moving object knows about the future motion plans of
other objects in the system. One
situation is that each object knows the trajectories of each other object. The trajectories can be known by the objects
exchanging their trajectories, and trajectories of neighboring vehicles they
are aware of, as resources. Another
situation is that objects do not know the future expected trajectories of other
objects; and there can be intermediate situations where some trajectories are
known but some are not. In each one of
these situations the propagation mechanism is different.
Finally, to propagate the answer
back to the query originator there can be several strategies. First, each moving object can send to the
query originator, O, the resources of R it is aware of in turn, O consolidates
the results (e.g. eliminates duplicates).
Second possibility is that a leader is elected in the region p; the
leader collects and consolidates the answers of the responding vehicles, before
delivering them to O.
NETWORKING:
Traditional MANET routing protocols are not suited to the high mobility
environment of vehicular networks. For
deployment in vehicular networks, topology- based routing protocols would
require a large number of routing states and incur large routing overheads for
updating topology changes. For example, a vehicle would query which locations
ahead have average speed below a specific threshold, rather than the average
speed of a particular vehicle.
PRIVACY AND SECURITY
Important privacy concerns
arise when a vehicle has to provide itslocation or future trajectory. In our case, this situation occurs when a
vehicle generates a query and needs to specify where the answer needs to be
returned. Anonymization techniques can
be used to address this problem.
Security issues arise in the economic model to prevent
cheating,to prevent vehicle from generating fictitious resources.
THE FUTURE:
With the rapid technological advancements
in mobile computing the future of data
on the road in intelligent transportation systems looks increasingly exciting. This scary concept of a world full of
inanimate zombies sitting, locked to their mobile stations, accessing every
sphere of their lives via the computer screen becomes ever more real as
technology, especially in the field of mobile data communications, rapidly
improves as shown below Using the mobile data communication technologies
discussed, this mobility may be pushed to extreme.
BENEFITS:
q
improving the data collection process
q
improving data accuracy
q
reducing paperwork
q
enforcing collection of more completed
information
q
facilitating collection of more useful
information
q
elimination redundant data entry
q
reducing administrative costs
q
reducing billing errors
q
reducing data backlog
q
improving information flow
q
allowing faster adaptation to changing business
conditions
q
increasing responsiveness and customer
satisfaction
CONCLUSION:
In this paper we devised a model for
dissemination of spatio-temporal resources in an infrastructure-less
environment, in which the database is distributed among the moving objects. The moving objects also serve as routers of
queries and answers. We discussed two
possible resource dissemination algorithms which differ in their treatment of
invalidation messages.The future of Mobile Computing is very promising indeed,
although technology may go too far, causing detriment to society.
REFERENCES:
[1] J. Haarsen, M. Nahshineh, J. Inouye, O.J. Joeresson, and W.Allen
ACM Mobile computing and communications.
[2] X, Chen, A.L. Murphy, Enabling Disconnected Transitive
Communication in Mobile Ad Hoc Networks, ACM principals of Mobile computing,
[3] J.Vu and F.Dai, “Mobility Management and its application in
efficient broad casting in mobile networks.
[4] V. Rodople and T.H. Meng, “Minimum Engg Mobile Wireless Networks,
IEEE JSAC, Vol-17 Aug –1999.
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