Synchronization in Distributed Systems

Sampath, Amritha; Tripti, C.

doi:10.1007/978-3-642-31513-8_43

Cited by 15 publications

(10 citation statements)

References 7 publications

(11 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is well known that strict time synchronization for distributed devices is a difficult problem [20]. There are residue synchronization offsets between them.…”

Section: Basic Schemementioning

confidence: 99%

Practical Secret Key Agreement for Full-Duplex Near Field Communications

Jin

Deng

et al. 2016

IEEE Trans. on Mobile Comput.

View full text Add to dashboard Cite

Near Field Communication (NFC) is a promising short distance radio communication technology for many useful applications. Although its communication range is short, NFC alone does not guarantee secure communication and is subject to security attacks, such as eavesdropping attack. Generating a shared key and using symmetric key cryptography to secure the communication between NFC devices is a feasible solution to prevent various attacks. However, conventional Diffie-Hellman key agreement protocol is not preferable for resource constrained NFC devices due to its extensive computational overhead and energy consumption. In this paper, we propose a practical, fast and energy-efficient key agreement scheme, which uses random bits transmission with waveform shaking, for NFC devices by exploiting its off-the-shelf full-duplex capability. In the proposed method, two devices send random bits to each other simultaneously without strict synchronization or perfect match of amplitude and phase. On the contrary, the method randomly introduces synchronization offset and mismatch of amplitude and phase for each bit transmission in order to prevent a passive attacker from determining the generated key. A shared bit can be established when two devices send different bits. We conduct theoretical analysis on the correctness and security strength of the method, and extensive simulations to evaluate its effectiveness. We build a testbed based on USRP software defined radio and conduct proof-of-concept experiments to evaluate the method in a real-world environment. It shows that the proposed method achieves a high key generation rate of about 26kbps and is immune to eavesdropping attack even when the attacker is within several centimeters from the legitimate devices. The proposed method is a practical, fast, energy-efficient, and secure key agreement scheme for resource-constrained NFC devices.

show abstract

“…It is well known that strict time synchronization for distributed devices is a difficult problem [20]. There are residue synchronization offsets between them.…”

Section: Basic Schemementioning

confidence: 99%

Practical Secret Key Agreement for Full-Duplex Near Field Communications

Jin

Deng

et al. 2016

IEEE Trans. on Mobile Comput.

View full text Add to dashboard Cite

show abstract

“…These online synchronization methods adjust the internal clock of the components during the monitoring process. Online synchronization uses several strategies, usually based in messages exchange and calculations on timestamps, for estimating and removing of clock's skew and offset [37], [38]. In a common online mechanism, such as NTP [39], a node could receive one or more messages with information about reference clock and/or local offset, and it can use this information for adjusting its internal clock.…”

Section: B Synchronization In Wsn Distributed Monitoringmentioning

confidence: 99%

HMP: A Hybrid Monitoring Platform for Wireless Sensor Networks Evaluation

et al. 2019

View full text Add to dashboard Cite

This work was supported by the Agencia Estatal de Investigación from the Spanish Ministerio de Economía, Industria y Competitividad, through the project Hacia el hospital inteligente: Investigación en el diseño de una plataforma basada en Internet de las Cosas y su aplicación en la mejora del cumplimiento de higiene de manos, under Grant DPI2016-80303-C2-1-P. The project covers the costs of publishing in open access.

show abstract

“…It is clear that if an event occurs at 6:42, then it happens before another event that occurs at 6:45. Unfortunately, accurately measuring time in a distributed system is infeasible [26,29,30]. Clocks on different servers within a distributed system drift apart, so servers cannot agree on a single global notion of time, and thus they cannot agree on a single global total order of events that respects the real time ordering of events.…”

Section: Background 21 Causalitymentioning

confidence: 99%

Debugging Distributed Systems with Why-Across-Time Provenance

Whittaker

Teodoropol

Alvaro

et al. 2018

Proceedings of the ACM Symposium on Cloud Computing

View full text Add to dashboard Cite

Systematically reasoning about the fine-grained causes of events in a real-world distributed system is challenging. Causality, from the distributed systems literature, can be used to compute the causal history of an arbitrary event in a distributed system, but the event's causal history is an overapproximation of the true causes. Data provenance, from the database literature, precisely describes why a particular tuple appears in the output of a relational query, but data provenance is limited to the domain of static relational databases. In this paper, we present wat-provenance: a novel form of provenance that provides the benefits of causality and data provenance. Given an arbitrary state machine, watprovenance describes why the state machine produces a particular output when given a particular input. This enables system developers to reason about the causes of events in real-world distributed systems. We observe that automatically extracting the wat-provenance of a state machine is often infeasible. Fortunately, many distributed systems components have simple interfaces from which a developer can directly specify wat-provenance using a technique we call wat-provenance specifications. Leveraging the theoretical foundations of wat-provenance, we implement a prototype distributed debugging framework called Watermelon.Returning to our example above, the why-provenance of the (Michael Jordan) tuple is the set {J 1 , J 2 } where J 1 = {(ecodd, jumpman), (jumpman, Michael Jordan)} J 2 = {(ecodd, mlpro), (mlpro, Michael Jordan)} J 1 and J 2 are minimal witnesses, so the why-provenance and minimal why-provenance of t = (Michael Jordan) are the same.

show abstract

Synchronization in Distributed Systems

Cited by 15 publications

References 7 publications

Practical Secret Key Agreement for Full-Duplex Near Field Communications

Practical Secret Key Agreement for Full-Duplex Near Field Communications

HMP: A Hybrid Monitoring Platform for Wireless Sensor Networks Evaluation

Debugging Distributed Systems with Why-Across-Time Provenance

Contact Info

Product

Resources

About