Pub Date : 2022-07-01DOI: 10.1109/ICDCS54860.2022.00150
J. M. Solé, Sergi Miralles Nogués, R. P. Centelles, Felix Freitag
LoRa has become popular in the Internet of Things (IoT) domain as a Low Power, Wide Area Network (LPWAN) radio technology providing low-power and long-range communication. In a typical IoT application, the LoRaWAN architecture is applied, where LoRa end nodes communicate their data to a gateway, which then over the Internet sends these data to a cloud-based service for further processing. However, LoRa can also be used standalone for the communication between LoRa nodes forming a mesh network. In this demo paper we present a library called LoRaMesher, which runs on LoRa nodes and forms a mesh network among these nodes. By implementing a distance vector routing protocol, LoRaMesher enables two nodes to communicate data packets with each other while the other nodes in the mesh network operate as routers. LoRaMesher can open the possibility for new distributed applications hosted only on such tiny IoT nodes.
{"title":"Demonstration of a library prototype to build LoRa mesh networks for the IoT","authors":"J. M. Solé, Sergi Miralles Nogués, R. P. Centelles, Felix Freitag","doi":"10.1109/ICDCS54860.2022.00150","DOIUrl":"https://doi.org/10.1109/ICDCS54860.2022.00150","url":null,"abstract":"LoRa has become popular in the Internet of Things (IoT) domain as a Low Power, Wide Area Network (LPWAN) radio technology providing low-power and long-range communication. In a typical IoT application, the LoRaWAN architecture is applied, where LoRa end nodes communicate their data to a gateway, which then over the Internet sends these data to a cloud-based service for further processing. However, LoRa can also be used standalone for the communication between LoRa nodes forming a mesh network. In this demo paper we present a library called LoRaMesher, which runs on LoRa nodes and forms a mesh network among these nodes. By implementing a distance vector routing protocol, LoRaMesher enables two nodes to communicate data packets with each other while the other nodes in the mesh network operate as routers. LoRaMesher can open the possibility for new distributed applications hosted only on such tiny IoT nodes.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122145130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud data storage relies on efficient cache systems to offer high performance for intensive reads/writes on big data. Due to the large data volume of cloud data storage and the limited capacity of DRAM, current cloud vendors prefer to use SSDs (Solid State Drives) but not DRAM to build the cache system. However, traditional SSDs have a serious over-provisioning problem and a high cost in garbage collection. Thus, the performance of SSD-based cache systems will drop quickly when the usage of SSDs increases. Recently, Zoned Namespaces (ZNS) SSDs have emerged as a hot topic in both academics and industries. Compared to conventional SSDs, ZNS SSDs have the advantages of less overhead of garbage collection and lower over-provisioning costs. Therefore, ZNS SSDs have been a better candidate for the cache system for cloud storage. However, ZNS SSDs only accept sequential writes, and the zones inside ZNS SSDs need to be carefully managed to maximize the advantages of ZNS SSDs. Therefore, making the cache system adapt to ZNS SSDs is becoming a challenging issue. In this paper, we demonstrate ZonedStore, a novel ZNS-aware cache system for cloud data storage. After a brief introduction to the architecture of ZonedStore, we present the key designs of ZonedStore, including a Zone Manager to control the space allocation and operations on ZNS SSDs, a Multi-Layer Buffer Manager, and an In-Memory Concurrent Index to accelerate accesses. Finally, we present a case study to demonstrate the working process and performance of ZonedStore.
{"title":"ZonedStore: A Concurrent ZNS-Aware Cache System for Cloud Data Storage","authors":"Yanqi Lv, Peiquan Jin, Xiaoliang Wang, Ruicheng Liu, Liming Fang, Yuanjin Lin, Kuankuan Guo","doi":"10.1109/ICDCS54860.2022.00148","DOIUrl":"https://doi.org/10.1109/ICDCS54860.2022.00148","url":null,"abstract":"Cloud data storage relies on efficient cache systems to offer high performance for intensive reads/writes on big data. Due to the large data volume of cloud data storage and the limited capacity of DRAM, current cloud vendors prefer to use SSDs (Solid State Drives) but not DRAM to build the cache system. However, traditional SSDs have a serious over-provisioning problem and a high cost in garbage collection. Thus, the performance of SSD-based cache systems will drop quickly when the usage of SSDs increases. Recently, Zoned Namespaces (ZNS) SSDs have emerged as a hot topic in both academics and industries. Compared to conventional SSDs, ZNS SSDs have the advantages of less overhead of garbage collection and lower over-provisioning costs. Therefore, ZNS SSDs have been a better candidate for the cache system for cloud storage. However, ZNS SSDs only accept sequential writes, and the zones inside ZNS SSDs need to be carefully managed to maximize the advantages of ZNS SSDs. Therefore, making the cache system adapt to ZNS SSDs is becoming a challenging issue. In this paper, we demonstrate ZonedStore, a novel ZNS-aware cache system for cloud data storage. After a brief introduction to the architecture of ZonedStore, we present the key designs of ZonedStore, including a Zone Manager to control the space allocation and operations on ZNS SSDs, a Multi-Layer Buffer Manager, and an In-Memory Concurrent Index to accelerate accesses. Finally, we present a case study to demonstrate the working process and performance of ZonedStore.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122693086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICDCS54860.2022.00048
Yiming Zeng, Yaodong Huang, Zhen Liu, Ji Liu
Edge caching is an effective way to reduce congestion and latency in 5G networks. Non-volatile memory (NVM) devices are developing fast, with the potential of fast access, and higher endurance versus traditional storage devices, to further boost mobile data offloading efficiency in 5G networks. This paper studies how to effectively use the two-layer storage system (NVM-enhanced) in 5G edge caching. We first model an edge caching optimization problem with NVM storage devices included and develop a parallel distributed algorithm with guaranteed convergence in joint caching and routing decisions. A fully decentralized algorithm for scenarios without any coordination is further developed which also guarantees the convergence. Real-world trace-driven simulations and experiments over a small-scale system demonstrate that NVM significantly boosts the performance of edge caching and the proposed algorithms outperform the existing ones.
{"title":"Distributed and Decentralized Edge Caching in 5G Networks Using Non-Volatile Memory Systems","authors":"Yiming Zeng, Yaodong Huang, Zhen Liu, Ji Liu","doi":"10.1109/ICDCS54860.2022.00048","DOIUrl":"https://doi.org/10.1109/ICDCS54860.2022.00048","url":null,"abstract":"Edge caching is an effective way to reduce congestion and latency in 5G networks. Non-volatile memory (NVM) devices are developing fast, with the potential of fast access, and higher endurance versus traditional storage devices, to further boost mobile data offloading efficiency in 5G networks. This paper studies how to effectively use the two-layer storage system (NVM-enhanced) in 5G edge caching. We first model an edge caching optimization problem with NVM storage devices included and develop a parallel distributed algorithm with guaranteed convergence in joint caching and routing decisions. A fully decentralized algorithm for scenarios without any coordination is further developed which also guarantees the convergence. Real-world trace-driven simulations and experiments over a small-scale system demonstrate that NVM significantly boosts the performance of edge caching and the proposed algorithms outperform the existing ones.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129666976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICDCS54860.2022.00052
Le Yu, Shufan Zhang, Lu Zhou, Yan Meng, Suguo Du, Haojin Zhu
As geo-location data has been increasingly adopted as a high-profile feature in targeted advertising, exposing user real locations to untrusted cloud services or advertisers has raised severe privacy concerns. To protect location privacy with formal guarantee, a wide-stretched line of recent studies focuses on injecting controlled geo-indistinguishability (geo-IND) noise as per each location exposure. However, in advertising, over the course of 2 years, a single user can report and contribute near 1k location data points on average, which allows a longitudinal attacker to infer some statistics from the perturbed locations.In this study, we demonstrate the above-mentioned privacy risk via revealing an inference attack mechanism, coined as a longitudinal location exposure attack. This novel attack illustrates the possibility of recovering 75%∼90% of user top-1 locations (within only 200-meter range) among 37k users. In light of this deficiency, we propose a novel edge-assisted location privacy protection system, entitled Edge-PrivLocAd, that is adapted to location-based advertising. The novelty of Edge-PrivLocAd stems from our n-fold Gaussian mechanism, which adds permanent noise to the statistical user location profile and thus can defend against longitudinal attackers while balancing the privacy-utility trade-off. In addition, our system incorporates a posterior-based sampling technique into the location re-mapping process, that boosts location utility without privacy loss. We develop a fully-functioning prototype and empirically evaluate the proposed system. Our experimental results show that Edge-PrivLocAd is practical and scalable in real-world scenarios.
{"title":"Thwarting Longitudinal Location Exposure Attacks in Advertising Ecosystem via Edge Computing","authors":"Le Yu, Shufan Zhang, Lu Zhou, Yan Meng, Suguo Du, Haojin Zhu","doi":"10.1109/ICDCS54860.2022.00052","DOIUrl":"https://doi.org/10.1109/ICDCS54860.2022.00052","url":null,"abstract":"As geo-location data has been increasingly adopted as a high-profile feature in targeted advertising, exposing user real locations to untrusted cloud services or advertisers has raised severe privacy concerns. To protect location privacy with formal guarantee, a wide-stretched line of recent studies focuses on injecting controlled geo-indistinguishability (geo-IND) noise as per each location exposure. However, in advertising, over the course of 2 years, a single user can report and contribute near 1k location data points on average, which allows a longitudinal attacker to infer some statistics from the perturbed locations.In this study, we demonstrate the above-mentioned privacy risk via revealing an inference attack mechanism, coined as a longitudinal location exposure attack. This novel attack illustrates the possibility of recovering 75%∼90% of user top-1 locations (within only 200-meter range) among 37k users. In light of this deficiency, we propose a novel edge-assisted location privacy protection system, entitled Edge-PrivLocAd, that is adapted to location-based advertising. The novelty of Edge-PrivLocAd stems from our n-fold Gaussian mechanism, which adds permanent noise to the statistical user location profile and thus can defend against longitudinal attackers while balancing the privacy-utility trade-off. In addition, our system incorporates a posterior-based sampling technique into the location re-mapping process, that boosts location utility without privacy loss. We develop a fully-functioning prototype and empirically evaluate the proposed system. Our experimental results show that Edge-PrivLocAd is practical and scalable in real-world scenarios.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128982739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICDCS54860.2022.00137
Bowei Zhang, Xiaoliang Wang, Ru Xie, Huazhe Zhang, Frank Jiang
The selfish On-Board-Unit (OBU) attacks Vehicular Ad-Hoc Network (VANET) by various attacks for profit. However, many existing methods are based on the principle of direct reciprocity for communication, and when an attack occurs, it is easy to crash in the case of large-scale networks. In order to reduce the number of attackers in the vehicle ad-hoc network and restrain the attack motivation of the OBUs, we propose an indirect reciprocal incentive mechanism based on reputation to encourage the OBUs in the VANET to help each other. Since most OBUs are in great need of network services, including potential attackers, when the loss of network services is far greater than the illegal benefits of their attacks, selfish and rational OBU will give up attacks and take desirable behavior. In addition, to prevent some attacks from tampering with information, we also apply blockchain technology to record the behavior of OBU. The indirect reciprocity process of each OBU in VANET can be regarded as a Markov Decision Process (MDP). In order to restrain the attack motivation of selfish nodes and communicate normally without knowing the attack model, an algorithm based on Deep Reinforcement Learning (DRL) is proposed to suppress attack motivation, so as to activate OBU learning in dynamic environment and make wise decisions. Finally, through a large number of simulation experiments, the performance of our proposed algorithm is obviously better than that of the baseline strategy, and is verified by the simulation results.
{"title":"Demo:Dynamic Suppression of Selfish Node Attack Motivation in the Process of VANET Communication","authors":"Bowei Zhang, Xiaoliang Wang, Ru Xie, Huazhe Zhang, Frank Jiang","doi":"10.1109/ICDCS54860.2022.00137","DOIUrl":"https://doi.org/10.1109/ICDCS54860.2022.00137","url":null,"abstract":"The selfish On-Board-Unit (OBU) attacks Vehicular Ad-Hoc Network (VANET) by various attacks for profit. However, many existing methods are based on the principle of direct reciprocity for communication, and when an attack occurs, it is easy to crash in the case of large-scale networks. In order to reduce the number of attackers in the vehicle ad-hoc network and restrain the attack motivation of the OBUs, we propose an indirect reciprocal incentive mechanism based on reputation to encourage the OBUs in the VANET to help each other. Since most OBUs are in great need of network services, including potential attackers, when the loss of network services is far greater than the illegal benefits of their attacks, selfish and rational OBU will give up attacks and take desirable behavior. In addition, to prevent some attacks from tampering with information, we also apply blockchain technology to record the behavior of OBU. The indirect reciprocity process of each OBU in VANET can be regarded as a Markov Decision Process (MDP). In order to restrain the attack motivation of selfish nodes and communicate normally without knowing the attack model, an algorithm based on Deep Reinforcement Learning (DRL) is proposed to suppress attack motivation, so as to activate OBU learning in dynamic environment and make wise decisions. Finally, through a large number of simulation experiments, the performance of our proposed algorithm is obviously better than that of the baseline strategy, and is verified by the simulation results.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"532 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117220548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICDCS54860.2022.00057
Hongli Lu, Guangping Xu, C. Sung, Salwa Mostafa, Yulei Wu
Edge computing is the next-generation computing paradigm that brings the processing capability closer to the location where it is needed. 5G and beyond 5G aim to achieve substantial improvement for the performance of edge computing in terms of e.g. higher throughput and lower latency. Smart base stations are often attached with edge datacenters consisting of many edge servers equipped with computing and storage capabilities. These servers are used to execute offloaded tasks from edge equipment such as Internet of Things. It is important to have an efficient offloading algorithm that can guarantee specific service-level objectives (SLOs) by assigning tasks to appropriate edge servers. Traditional offloading schemes such as static and learning-based algorithms either have limited performance or result in high overhead for task assignment to servers. In this paper, we propose an efficient game-theoretical scheduling algorithm for offloaded tasks at edge datacenters. The core contribution of the algorithm is to design a public goods investment model for edge servers. Based on the model, we design a lightweight scheduling algorithm to reduce the average load of edge servers and enhance the stability of edge datacenter systems. Experimental results demonstrate the significant benefits of the proposed algorithm in reducing the response latency of tasks and balancing the workload of edge servers.
{"title":"A Game Theoretical Balancing Approach for Offloaded Tasks in Edge Datacenters","authors":"Hongli Lu, Guangping Xu, C. Sung, Salwa Mostafa, Yulei Wu","doi":"10.1109/ICDCS54860.2022.00057","DOIUrl":"https://doi.org/10.1109/ICDCS54860.2022.00057","url":null,"abstract":"Edge computing is the next-generation computing paradigm that brings the processing capability closer to the location where it is needed. 5G and beyond 5G aim to achieve substantial improvement for the performance of edge computing in terms of e.g. higher throughput and lower latency. Smart base stations are often attached with edge datacenters consisting of many edge servers equipped with computing and storage capabilities. These servers are used to execute offloaded tasks from edge equipment such as Internet of Things. It is important to have an efficient offloading algorithm that can guarantee specific service-level objectives (SLOs) by assigning tasks to appropriate edge servers. Traditional offloading schemes such as static and learning-based algorithms either have limited performance or result in high overhead for task assignment to servers. In this paper, we propose an efficient game-theoretical scheduling algorithm for offloaded tasks at edge datacenters. The core contribution of the algorithm is to design a public goods investment model for edge servers. Based on the model, we design a lightweight scheduling algorithm to reduce the average load of edge servers and enhance the stability of edge datacenter systems. Experimental results demonstrate the significant benefits of the proposed algorithm in reducing the response latency of tasks and balancing the workload of edge servers.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117229782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICDCS54860.2022.00073
Sihan Yu, ChunChih Lin, Xiaonan Zhang, Linke Guo
The wide deployment of IoT devices has resulted in a critical shortage of spectrum resources. Many IoT devices coexist on the same spectrum band, where the network performance is always degraded. As a promising solution, the Cross-Technology Communication (CTC) enables the direct communication among heterogeneous IoT devices. Unfortunately, the emerging cross-technology attacks have demonstrated their high success rates in terms of spoofing the end IoT devices or jamming the communication channels. In this paper, we investigate a novel cross-technology jamming issue for a distributed heterogeneous IoT system. Compared with traditional jamming methods, the cross-technology jammer has a much higher jamming power, wider jamming bandwidth, and stronger stealthiness, all of which deserve a complete re-thinking of defensive mechanisms. Therefore, we propose a hybrid anti-jamming scheme that jointly considers frequency hopping and power control techniques. Specifically, we model the anti-jamming process as a Markov Decision Process (MDP) and adopt Deep Q-Network (DQN) to find the optimal strategy. Extensive real-world experiments show that the goodput (payload data) of our anti-jamming scheme can achieve up to 2X and 1.39X than the passive and random anti-jamming approaches, respectively. In particular, our anti-jamming scheme provides 78% of goodput with the presence of a cross-technology jammer, outperforming existing passive and random anti-jamming scheme designs at 37.6% and 54.1%.
{"title":"Defending against Cross-Technology Jamming in Heterogeneous IoT Systems","authors":"Sihan Yu, ChunChih Lin, Xiaonan Zhang, Linke Guo","doi":"10.1109/ICDCS54860.2022.00073","DOIUrl":"https://doi.org/10.1109/ICDCS54860.2022.00073","url":null,"abstract":"The wide deployment of IoT devices has resulted in a critical shortage of spectrum resources. Many IoT devices coexist on the same spectrum band, where the network performance is always degraded. As a promising solution, the Cross-Technology Communication (CTC) enables the direct communication among heterogeneous IoT devices. Unfortunately, the emerging cross-technology attacks have demonstrated their high success rates in terms of spoofing the end IoT devices or jamming the communication channels. In this paper, we investigate a novel cross-technology jamming issue for a distributed heterogeneous IoT system. Compared with traditional jamming methods, the cross-technology jammer has a much higher jamming power, wider jamming bandwidth, and stronger stealthiness, all of which deserve a complete re-thinking of defensive mechanisms. Therefore, we propose a hybrid anti-jamming scheme that jointly considers frequency hopping and power control techniques. Specifically, we model the anti-jamming process as a Markov Decision Process (MDP) and adopt Deep Q-Network (DQN) to find the optimal strategy. Extensive real-world experiments show that the goodput (payload data) of our anti-jamming scheme can achieve up to 2X and 1.39X than the passive and random anti-jamming approaches, respectively. In particular, our anti-jamming scheme provides 78% of goodput with the presence of a cross-technology jammer, outperforming existing passive and random anti-jamming scheme designs at 37.6% and 54.1%.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116001819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICDCS54860.2022.00022
Mingzhe Li, You-lin Li, Jin Zhang, Wei Wang
Sharding is a promising way to achieve blockchain scalability, increasing the throughput by partitioning nodes into multiple smaller groups, splitting the workload. However, when tackling the increasingly important smart contracts, existing blockchain sharding protocols do not scale well. They usually require complex multi-round cross-shard consensus protocols for contract execution and extensive cross-shard communication during state transmission, mainly because that each shard stores and executes an isolated, disjoint subset of contracts. In this paper, we present Jenga, a novel sharding-based approach for efficient smart contract processing. Its main idea is to break the isolation between shards by orchestrating the logic storage, state storage, and execution of smart contracts. In Jenga, all shards share the logic for all contracts. Therefore, multiple contracts involved in a smart contract transaction can be executed together by the same shard within one round. Moreover, different shards store distinct states (named state shards), several "orthogonal" execution channels are established based on the state shards, where each channel overlaps with all shards. Each node simultaneously belongs to a shard and an "orthogonal" channel, different channels execute different contracts. Therefore, via the overlapped nodes, the contract states can be directly broadcast between the state shards and the execution channels without additional cross-shard communication. We implement Jenga and evaluation results show that it provides outstanding performance gains in terms of throughput and transaction confirmation latency.
{"title":"Jenga: Orchestrating Smart Contracts in Sharding-Based Blockchain for Efficient Processing","authors":"Mingzhe Li, You-lin Li, Jin Zhang, Wei Wang","doi":"10.1109/ICDCS54860.2022.00022","DOIUrl":"https://doi.org/10.1109/ICDCS54860.2022.00022","url":null,"abstract":"Sharding is a promising way to achieve blockchain scalability, increasing the throughput by partitioning nodes into multiple smaller groups, splitting the workload. However, when tackling the increasingly important smart contracts, existing blockchain sharding protocols do not scale well. They usually require complex multi-round cross-shard consensus protocols for contract execution and extensive cross-shard communication during state transmission, mainly because that each shard stores and executes an isolated, disjoint subset of contracts. In this paper, we present Jenga, a novel sharding-based approach for efficient smart contract processing. Its main idea is to break the isolation between shards by orchestrating the logic storage, state storage, and execution of smart contracts. In Jenga, all shards share the logic for all contracts. Therefore, multiple contracts involved in a smart contract transaction can be executed together by the same shard within one round. Moreover, different shards store distinct states (named state shards), several \"orthogonal\" execution channels are established based on the state shards, where each channel overlaps with all shards. Each node simultaneously belongs to a shard and an \"orthogonal\" channel, different channels execute different contracts. Therefore, via the overlapped nodes, the contract states can be directly broadcast between the state shards and the execution channels without additional cross-shard communication. We implement Jenga and evaluation results show that it provides outstanding performance gains in terms of throughput and transaction confirmation latency.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124423655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICDCS54860.2022.00028
Ouri Poupko, E. Shapiro, Nimrod Talmon
Mainstream cryptocurrencies, based on proof of work or stake, require paying miners for the capital-intensive execution of a consensus protocol, and hence are unsuitable as a foundation for capital-free digital communities and for the bootstrap of a grassroots digital society. We aim to adapt and adjust the concepts, tools and technologies developed by the cryptocurrencies ecosystem, together with related networking technologies, into a foundation for a healthy grassroots digital economy and society. In this context we present the design and proof-of-concept implementation of a self-sovereign digital agent (ssDA), as an essential building block for a grassroots digital economy and society. The ssDA serves as a party, on behalf of its sovereign—a person—in digital social contracts, which are smart contracts among vetted participants, who are its sovereign in that they jointly execute the contract with an egalitarian consensus protocol. Digital social contracts may realize social networks, sharing economy applications, social governance of a digital community, and more. The ssDA is a software application that allows a person to partake in multiple digital social contracts simultaneously. Participation in a contract can be realized by initiating it or by being invited to it. Extra confidence in the integrity of the data is achieved by each person maintaining a blockchain containing all the person’s transactions in all contracts.
{"title":"Self-Sovereign Digital Agents for a Grassroots Digital Society","authors":"Ouri Poupko, E. Shapiro, Nimrod Talmon","doi":"10.1109/ICDCS54860.2022.00028","DOIUrl":"https://doi.org/10.1109/ICDCS54860.2022.00028","url":null,"abstract":"Mainstream cryptocurrencies, based on proof of work or stake, require paying miners for the capital-intensive execution of a consensus protocol, and hence are unsuitable as a foundation for capital-free digital communities and for the bootstrap of a grassroots digital society. We aim to adapt and adjust the concepts, tools and technologies developed by the cryptocurrencies ecosystem, together with related networking technologies, into a foundation for a healthy grassroots digital economy and society. In this context we present the design and proof-of-concept implementation of a self-sovereign digital agent (ssDA), as an essential building block for a grassroots digital economy and society. The ssDA serves as a party, on behalf of its sovereign—a person—in digital social contracts, which are smart contracts among vetted participants, who are its sovereign in that they jointly execute the contract with an egalitarian consensus protocol. Digital social contracts may realize social networks, sharing economy applications, social governance of a digital community, and more. The ssDA is a software application that allows a person to partake in multiple digital social contracts simultaneously. Participation in a contract can be realized by initiating it or by being invited to it. Extra confidence in the integrity of the data is achieved by each person maintaining a blockchain containing all the person’s transactions in all contracts.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125179404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICDCS54860.2022.00141
Berat Can Senel, Maxime Mouchet, Justin Cappos, T. Friedman, Olivier Fourmaux, R. McGeer
The EdgeNet software is free, open-source, liberally licensed code that extends the Kubernetes container orchestration system to the edge cloud. We use this code to run the EdgeNet testbed, an internet-scale edge cloud for distributed systems researchers. This demonstration showcases three features of EdgeNet: its multitenancy model, its multi-provider aspect, and its geographically-based selective deployment capability. Multitenancy allows multiple teams to use the platform concurrently; being multi-provider, independent contributors can make nodes available to the platform; and selective deployment facilitates location-based placement of software. Under our guidance, demo participants invoke the Kubernetes command-line interface to use the testbed. In so doing, they get experience with the testbed, which they can continue to use afterwards. They also gain insight into how the demonstrated features are useful for edge cloud container deployment in general. Participants who volunteer to help EdgeNet nodes receive Odroid devices to host in their homes or workplaces.
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