We study the problem of efficiently disseminating authenticated blockchain information from blockchain nodes (servers) to Internet of Things (IoT) devices, through a wireless base station (BS). In existing blockchain protocols, upon generation of a new block, each IoT device receives a copy of the block header, authenticated via digital signature by one or more trusted servers. Since it relies on unicast transmissions, the required communication resources grow linearly with the number of IoT devices. We propose a more efficient scheme, in which a single copy of each block header is multicasted, together with the signatures of servers. In addition, if IoT devices tolerate a delay, we exploit the blockchain structure to amortize the authentication in time, by transmitting only a subset of signature in each block period. Finally, the BS sends redundant information, via a repetition code, to deal with the unreliable wireless channel, with the aim of decreasing the amount of feedback required from IoT devices. Our analysis shows the trade-off between timely authentication of blocks and reliability of the communication, depending on the channel quality (packet loss rate), the block interaction, and the presence of forks in the blockchain. The numerical results show the performance of the scheme, that is a viable starting point to design new blockchain lightweight protocols.
The problem of reliable and authenticated multicasting of data streams is a well-investigated subject @cite_2 . Here, a message is authenticated when it is digitally signed by a trusted party and the signature is received. However, message and signature are not necessarily sent together. Hence, when a message is received, but not authenticated, it is considered useless.
@cite_2
2216201412 2166910390 68293075 2169363112
Error correction and message authentication are well studied in the literature, and various efficient solutions have been suggested and analyzed. This is however not the case for data streams in which the message is very long, possibly infinite, and not known in advance to the sender. Trivial solutions for error-correcting and authenticating data streams either suffer from a long delay at the receiver’s end or cannot perform well when the communication channel is noisy. Sender-initiated reliable multicast protocols based on the use of positive acknowledgments (ACKs) can suffer performance degradation as the number of receivers increases. This degradation is due to the fact that the sender must bear much of the complexity associated with reliable data transfer (e.g., maintaining state information and timers for each of the receivers and responding to receivers' ACKs). A potential solution to this problem is to shift the burden of providing reliable data transfer to the receivers-thus resulting in receiver-initiated multicast error control protocols based on the use of negative acknowledgments (NAKs). We determine the maximum throughputs for generic sender-initiated and receiver-initiated protocols for two classes of applications: (1) one-many applications where one participant sends data to a set of receivers and (2) many-many applications where all participants simultaneously send and receive data to from each other. We show that a receiver-initiated error control protocol which requires receivers to transmit NAKs point-to-point to the sender provides higher throughput than a sender-initiated counterpart for both classes of applications. We further demonstrate that, in the case of a one many application, replacing point-to-point transfer of NAKs with multicasting of NAKs coupled with a random backoff procedure provides a substantial additional increase in the throughput of a receiver-initiated error control protocol over a sender-initiated protocol. We also find, however, that such a modification leads to a throughput degradation in the case of many-many applications. In this work we consider the problem of secure data transmission on an acyclic multicast network. A new information theoretic model for security is proposed that defines the system as secure if an eavesdropper is unable to get any “meaningful” information about the source. The “wiretap” network model by Cai and Yeung in which no information of the source is made available to the eavesdropper is a special case in the new model. We consider the case when the number of independent messages available to the eavesdropper is less than the multicast capacity of the network. We show that under the new security requirements communication is possible at the multicast capacity. A linear transformation is provided for networks with a given linear code to make the system secure. The transformation needs to be done only at the source and the operations at the intermediate nodes remain unchanged. We also show that if random coding scheme is used the probability of the system being secure can be made arbitrarily close to one by coding over a large enough field. The problem of transmit beamforming to multiple cochannel multicast groups is considered, when the channel state is known at the transmitter and from two viewpoints: minimizing total transmission power while guaranteeing a prescribed minimum signal-to-interference-plus-noise ratio (SINR) at each receiver; and a "fair" approach maximizing the overall minimum SINR under a total power budget. The core problem is a multicast generalization of the multiuser downlink beamforming problem; the difference is that each transmitted stream is directed to multiple receivers, each with its own channel. Such generalization is relevant and timely, e.g., in the context of the emerging WiMAX and UMTS-LTE wireless networks. The joint problem also contains single-group multicast beamforming as a special case. The latter (and therefore also the former) is NP-hard. This motivates the pursuit of computationally efficient quasi-optimal solutions. It is shown that Lagrangian relaxation coupled with suitable randomization cochannel multicast power control yield computationally efficient high-quality approximate solutions. For a significant fraction of problem instances, the solutions generated this way are exactly optimal. Extensive numerical results using both simulated and measured wireless channels are presented to corroborate our main findings.