A complete scheme for distributed LU decomposition on wireless sensor networks

Abdelhak, Sherine; Abdelgawad, Ahmed; Ghosh, Soumik; Bayoumi, Magdy

doi:10.1109/mwscas.2010.5548844

Cited by 4 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In particular, according to (9), at SM j (1 ≤ j ≤ n) we have r j,j k j + r j,j+1 k j+1 + ... + r j,n k n = Q T P(j) (14) where r i,j is the element in the ith row and the jth column of R, and Q T P(j) is the jth element of Q T P. So, once the collector receives all the sets B j 's from SM n , it will compute Q T P and distribute the jth element to SM j . SM n can then obtain its honesty coefficient k n .…”

Section: Procedures 5 Distributed Qr Decompositionmentioning

confidence: 99%

See 1 more Smart Citation

Privacy-Preserving Energy Theft Detection in Smart Grids: A P2P Computing Approach

Salinas

2013

IEEE J. Select. Areas Commun.

View full text Add to dashboard Cite

In the U.S., energy theft causes about six billion dollar losses to utility companies (UCs) every year. With the smart grid being proposed to modernize current power grids, energy theft may become an even more serious problem since the "smart meters" used in smart grids are vulnerable to more types of attacks compared to traditional mechanical meters. Therefore, it is important to develop efficient and reliable methods to identify illegal users who are committing energy theft. Although some schemes have been proposed for the UCs to detect energy theft in power grids, they all require users to send their private information, e.g., load profiles or meter readings at certain times, to the UCs, which invades users' privacy and raises serious concerns about privacy, safety, etc. To the best of our knowledge, we are the first to investigate the energy theft detection problem considering users' privacy issues. Specifically, in this paper, utilizing peer-to-peer (P2P) computing, we propose three distributed algorithms to solve a linear system of equations (LSE) for users' "honesty coefficients". Extensive simulations are carried out and the results show that the proposed algorithms can efficiently and successfully identify the fraudulent users in the system.

show abstract

Section: Procedures 5 Distributed Qr Decompositionmentioning

confidence: 99%

“…More specifically, we propose to take advantage of distributed LU and QR decompositions to solve our LSE. Although some distributed algorithms for LU or QR decomposition [13] have been proposed in the literature, e.g., [14]- [17], they cannot preserve each node's private information.…”

mentioning

confidence: 99%