An Ef?cient Ride-Sharing Framework for Maximizing Shared Route

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.
Technologies
  • Android
  • .netMVC
  • PHP
  • Python
  • Java
  • Django

Abstract—Ride-sharing (RS) has great values in saving energy and alleviating traf?c pressure. Existing studies can be improved for better ef?ciency. Therefore, we propose a new ride-sharing model, where each driver has a requirement that if the driver shares a ride with a rider, the shared route percentage (i.e., the ratio of the shared route’s distance to the driver’s total travel distance) exceeds an expectation rate of the driver, e.g., 0.8. We consider two variants of this problem. The ?rst considers multiple drivers and multiple riders and aims to compute driver-rider pairs to maximize the overall shared route percentage (SRP). We model this problem as the maximum weighted bigraph matching problem, where the vertices are drivers and riders, edges are driver-rider pairs, and edge weights are driver-rider’s SRP. However, it is rather expensive to compute the SRP values for large numbers of driver-rider pairs on road networks. To address this problem, we propose an ef?cient method to prune many unnecessary driver-rider pairs and avoid computing the SRP values for every pair. To improve the ef?ciency, we propose an approximate method with error bound guarantee. The basic idea is that we compute an upper bound and a lower bound for each driver-rider pair in constant time. Then, we estimate an upper bound and a lower bound of the graph matching. Next, we select some driver-rider pairs, compute their real shortest-route distance, and update the lower and upper bounds of the maximum graph matching. We repeat above steps until the ratio of the upper bound to the lower bound is not larger than a given approximate rate. The second considers multiple drivers and a single rider and aims to ?nd the top-k drivers for the rider with the largest SRP. We ?rst prune a large number of drivers that cannot meet the SRP requirements. Then, we propose a best-?rst algorithm that progressively selects the drivers with high probability to be in the top-k results and prunes the drivers that cannot be in the top-k results. Extensive experiments on real-world datasets demonstrate the superiority of our method.

3 years ago


DOWNLOAD


Related Topics

Challenges in Storage and Retrival of Healthcare Data:Review of various NoSQL Technologies

ABSTRACT: In current digital Era, the volume of data that is being generated through various processes in the Health care industry has become unmanageable. More than structured data there are a lot of unstructured data that is being generated. Relevant research indicate that are many issues that ...

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.


Technologies
  • BigData
  • .netMVC
  • PHP
  • Python
  • Java
  • Django
  • HBase
  • Hadoop
Density Based Smart Traffic Control System Using Canny Edge Detection Algorithm for Congregating Traffic Information

Abstract—As the problem of urban traffic congestion intensifies, there is a pressing need for the introduction of advanced technology and equipment to improve the state-of-theart of traffic control. The current methods used such as timers or human control are proved to be inferior to alleviate th...

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.


Technologies
  • BigData
  • .netMVC
  • PHP
  • Python
  • Java
  • Django
  • HBase
  • Hadoop
  • Android
  • Laravel
A Utility-optimized Framework for Personalized Private Histogram Estimation

Abstract—Recently, local differential privacy (LDP), as a strong and practical notion, has been applied to deal with privacy issues in data collection. However, existing LDP-based strategies mainly focus on utility optimization at a single privacy level while ignoring various privacy preferences ...

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.


Technologies
  • BigData
  • .netMVC
  • PHP
  • Python
  • Java
  • Django
  • HBase
  • Hadoop
  • Android
  • Laravel
MasterPrint: Exploring the Vulnerability of Partial Fingerprint-based Authentication Systems

Abstract—This paper investigates the security of partial ?ngerprint-based authentication systems, especially when multiple ?ngerprints of a user are enrolled. A number of consumer electronic devices, such as smartphones, are beginning to incorporate ?ngerprint sensors for user authentication. The...

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.


Technologies
  • BigData
  • .netMVC
  • PHP
  • Python
  • Java
  • Django
  • HBase
  • Hadoop
  • Android
  • Laravel
Non-overlapping Subsequence Matching of Stream Synopses

Abstract—In this paper, we propose SUbsequence Matching framework with cell MERgence (SUMMER) for online subsequence matching between histogram-based stream synopsis structures under the dynamic time warping distance. Given a query synopsis pattern, SUMMER continuously identi?es all the matching ...

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.


Technologies
  • BigData
  • .netMVC
  • PHP
  • Python
  • Java
  • Django
  • HBase
  • Hadoop
  • Android
  • Laravel