Proceedings of the 21st International Conference on Distributed Computing and Networking最新文献

{"title":"Fully Compact Routing in Low Memory Self-Healing Trees","authors":"Armando Castañeda, Jonas Lefèvre, Amitabh Trehan","doi":"10.1145/3369740.3369786","DOIUrl":"https://doi.org/10.1145/3369740.3369786","url":null,"abstract":"The paper (Compact Routing Messages in Self-Healing Trees, TCS 2017) introduced CompactFTZ, the first self-healing compact routing algorithm that works in a distributed network with each node using only O(log n) words (i.e. O(log2 n) bits) memory and thus O(log n) sized messages. The routing uses only O(1) and O(log n) words routing table and packet labels respectively on a self-healing tree that also works using only O(1) words repairing the network in face of a strong adversary deleting nodes. This deterministic algorithm sets up its data structures in a preprocessing phase and then updates the required data structures in only O(1) parallel time per healing round during execution of the algorithm. However, CompactFTZ has no constraints in its preprocessing phase which could be done in distributed large memory or even centrally. In this paper, we correct that by developing the algorithms for preprocessing of CompactFTZ in a fully distributed manner using only O(log n) words memory in optimal time. In fact, the preprocessing for the self-healing tree (ForgivingTree) component takes only O(1) memory. We develop a local function which each node invokes to instantly compute and then relay its repair instructions (known as its Will) in only O(1) time. We formalise the low memory CONGEST model setting used in previous low memory algorithms (e.g.[24]); nodes' working memory is restricted to be much smaller (in our case, O(log n)) than the numbers of their neighbours to whom they communicate through their I/O ports. We expand the model to allow for non-contiguous ports (e.g. empty ports or neighbours unmarked or lost in dynamic settings) and adversarial order of inputs from neighbours. Besides the Wills, we set up the tree structures and traversals for the routing scheme using only O(log n) memory and O(D) parallel time, where D is the diameter. Thus, we devise the first self-healing compact routing algorithm that can be fully set up and executed in low memory.","PeriodicalId":240048,"journal":{"name":"Proceedings of the 21st International Conference on Distributed Computing and Networking","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115418773","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}

{"title":"bioMCS","authors":"Satyaki Roy, Nirnay Ghosh, Preetam Ghosh, Sajal K. Das","doi":"10.1145/3369740.3369788","DOIUrl":"https://doi.org/10.1145/3369740.3369788","url":null,"abstract":"Mobile crowdsensing (MCS) leverages the participation of active citizens and establishes a cost-effective sensing infrastructure using their devices. The MCS platform allocates sensing tasks, for which individual user reports are collected to enable decision making. Task sensing and communication not only consume user's device energy, but also spawn redundant data leading to network congestion and issues in data management at the platform's end. MCS, being a building block of sustainable smart city applications, must ensure judicious utilization of device energy and network resources. To address these challenges, this paper proposes a bio-inspired data transfer framework, bioMCS, deployed over a fog computing platform and capable of enforcing collaborative sensing among proximate users. bioMCS achieves energy efficiency and robustness through the topological properties of a biological network called transcriptional regulatory network. It employs collaborative sensing to further restrict device energy overhead by taking advantage of energy efficient device-to-device communications like Wi-Fi direct data transfer via group owner. We evaluate our framework through extensive simulation-based experiments and demonstrate that the bioMCS framework achieves better energy and network efficiency compared to individual user-centric data transfer mechanism.","PeriodicalId":240048,"journal":{"name":"Proceedings of the 21st International Conference on Distributed Computing and Networking","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117185379","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}

{"title":"Low-Latency Energy-Efficient Cyber-Physical Disaster System Using Edge Deep Learning","authors":"Yashwant Singh Patel, Sourasekhar Banerjee, R. Misra, Sajal K. Das","doi":"10.1145/3369740.3372752","DOIUrl":"https://doi.org/10.1145/3369740.3372752","url":null,"abstract":"Reported works on cyber-physical disaster systems (CPDS) deal with the assessment of loss and damage aftermath of a large-scale disaster such as earthquake, wildfire, and cyclone, etc. involves collecting data from the IoT devices sent to the cloud data centers for analysis, often causes high bandwidth usage with substantial delay. In our work, we have shown to eliminate bandwidth cost and reducing latency substantially suitable for post-disaster response for rescue operations. We propose a low-latency and energy-efficient CPDS applying cloud-IoT-edge by bringing intelligence and infer-encing proximity to the disaster site to detect the disaster events in real-time and inform to the rescue teams. The edge computing model of CPDS uses convolutional neural network (CNN) with MobileNetV2 lightweight model and gradient weighted class activation mapping (Grad-CAM++) to locate and quantify degree of the damage into classes- severe, mild, and no damage. We implemented CPDS on a real-world laboratory testbed that comprises resource-constrained edge devices (Raspberry Pi, smartphones, and PCs) and docker-based containerization of deep learning models and analyzed the computational complexity. With the rigorous experiments of the proposed approach, we evaluated the performance in terms of classification accuracy, energy saving, and end-to-end (E2E) delay comparing with the current state-of-the-art approaches.","PeriodicalId":240048,"journal":{"name":"Proceedings of the 21st International Conference on Distributed Computing and Networking","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123007591","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}

{"title":"Performance Considerations for Edge Blockchain Systems in Emerging 5G Data Networks","authors":"D. Krishnaswamy","doi":"10.1145/3369740.3372767","DOIUrl":"https://doi.org/10.1145/3369740.3372767","url":null,"abstract":"As edge computing applications become increasingly relevant to society, data processing and storage requirements are expected to increase at the 5G networked edge. At the same time, with the emergence of blockchain and distributed ledger technologies, one can provide support for trust, immutability, and transparency to share information among networked entities at the edge and in the cloud in 5G networks. A performance model for a permissioned private blockchain platform is developed. Depending on the latency sensitivity and throughput requirements of a 5G edge application, different possibilities are explored to provide support for blockchain technology at the edge. In particular, applications to 5G use-cases are considered, and lazy ledger decoupling between the 5G edge and the 5G cloud is proposed to meet edge latency constraints.","PeriodicalId":240048,"journal":{"name":"Proceedings of the 21st International Conference on Distributed Computing and Networking","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125154708","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}

{"title":"Dummy Generation-Based Privacy Preservation for Location-Based Services","authors":"Dilay Parmar, U. P. Rao","doi":"10.1145/3369740.3373805","DOIUrl":"https://doi.org/10.1145/3369740.3373805","url":null,"abstract":"Location-Based Services (LBS) are a type of applications, which requires user's location information as input in providing useful services [4]. Google Maps (Online Navigation Applications), Foursquare (Geo-Social Network), Strava (Fitness Applications), etc. are some of the examples of LBS applications. For all the LBS applications, privacy is a major concern. LBS user may not be interested in revealing its where-about information to anyone, not even to LBS provider.","PeriodicalId":240048,"journal":{"name":"Proceedings of the 21st International Conference on Distributed Computing and Networking","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116842771","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}

{"title":"A Novel Fuzzy Based Hybrid PSOGSA Algorithm in WSNs","authors":"Tanima Bhowmik, I. Banerjee, Anagha Bhattacharya","doi":"10.1145/3369740.3372776","DOIUrl":"https://doi.org/10.1145/3369740.3372776","url":null,"abstract":"Lifetime and energy consumption are the main objectives of wireless sensor networks (WSNs). The existing methodologies have certain inhibitions which limit their applications. Clustering optimization is a major technique in any wireless sensor networks to optimize energy efficiency. Clustering technique assembles the objects of comparable shape in one shape. This technique is the excellent data assembly model for WSN, and it handles the redundant data within the network. The selection of the cluster head is an important feature in the clustering technique, then cluster heads cumulative the data and transmits to sink. Here fuzzy logic control algorithm has been proposed with hybridized particle swarm optimization algorithm and gravitational search algorithm to select cluster heads in WSN (FHPSOGSA). The algorithm is used to merge the constraints like remaining energy, node degree and distance to sink and select the best appropriate nodes as Cluster Head (CH). Simulation outcome displays that the proposed algorithm (FHPSOGSA) is establish to yield best results over other conventional algorithms.","PeriodicalId":240048,"journal":{"name":"Proceedings of the 21st International Conference on Distributed Computing and Networking","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114304335","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}

{"title":"Suppressing Noisy Neighbours in 5G networks: An end-to-end NFV-based framework to detect and suppress noisy neighbours","authors":"Salil Akundi, Shailesh Prabhu, K. NithinUpadhyaB., S. Mondal","doi":"10.1145/3369740.3372768","DOIUrl":"https://doi.org/10.1145/3369740.3372768","url":null,"abstract":"The 'noisy neighbour problem' refers to situations arising in network function virtualization where one or more virtualized units (such as virtual machines or Docker containers) experience a degradation in performance due to the fact that some of the resources needed are occupied by other units on the same node. This degradation in performance could be caused due to several reasons including inefficient scheduling procedures or a lack of compute, memory or network resources. Due to the multivariate nature of such situations, detecting them is non-trivial and requires different techniques like machine-learning. A common way to optimize such scenarios is by means of virtual machine (VM) or container migration. However, the resources required for migration are limited. Furthermore, the migration process is computationally expensive and comes with longer latency. This paper proposes an algorithm to suppress noisy neighbours using a combination of dynamic CPU pinning (or CPU affinity) based on host processor utilization and load balancing based on dynamic network slicing. An end-to-end framework proposed in this paper detects and suppresses noisy neighbours leading to improvement in the overall system efficiency.","PeriodicalId":240048,"journal":{"name":"Proceedings of the 21st International Conference on Distributed Computing and Networking","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133247974","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}

{"title":"Dynamic Taxi Ride Sharing using Localized Communication","authors":"Haoxiang Yu, V. Raychoudhury, Shrawani Silwal","doi":"10.1145/3369740.3369776","DOIUrl":"https://doi.org/10.1145/3369740.3369776","url":null,"abstract":"With the rise of on-demand taxi services, like Uber, Lyft, etc., urban public transportation started to heavily depend on taxicabs. While increasing demand leads to passenger stranding, higher supply may result in traffic congestion. In order to strike a balance ride sharing plays an important role. However, scheduling a ride on-the-fly is extremely challenging and more so with increasing number of passengers. It is non-trivial to find a driving route for the taxi accommodating multiple passengers without extending their journey time beyond a pre-specified tolerance value. The spatiotemporal separation of passengers and high mobility of taxis even more complicates shared ride scheduling. Existing distributed ride sharing solutions failed to address the extremely dynamic nature of the underlying topology where taxis are continuously moving and hence, results in message loss. In this paper, we have proposed a purely distributed ride sharing algorithm aimed at addressing the dynamics of taxi topology using asynchronous localized communication between passengers and taxis. Empirical analysis using large scale single-user taxi ride records from Chicago, show that, our proposed algorithm, ensures a maximum of 76% success in ride sharing and a 97.5% taxi occupancy rate during peak operating hours.","PeriodicalId":240048,"journal":{"name":"Proceedings of the 21st International Conference on Distributed Computing and Networking","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133893252","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}

{"title":"Resolution of Blockchain Conflicts through Heuristics-based Game Theory and Multilayer Network Modeling","authors":"A. D. Stefano, D. Maesa, Sajal K. Das, P. Lio’","doi":"10.1145/3369740.3372914","DOIUrl":"https://doi.org/10.1145/3369740.3372914","url":null,"abstract":"A blockchain is a fully distributed system in which the user behavior, actions and decisions are crucial for its operation. This paper discusses how to handle conflict situations affecting a blockchain system. Specifically, we model two real-world conflict scenarios -- the Lazy Miner dilemma and the Impatient Seller dilemma -- by proposing a novel multi-layer framework coupled with a heuristics-based game-theoretic modeling. The multi-layer approach provides a way to include cross-modality integration (human quality factors, such as reliability) and human actions on the blockchain. We design a multi-agent game-theoretic methodology combined with some statistical estimators derived from the heuristics. Our model also includes the concept of homophily, a human-related factor connected to the similarity and frequency of interactions on the multi-layer network. Based on the heuristics, a dynamically evolving measure of weights is further defined such that an agent increases or decreases the link weights to its neighbours according to the experienced payoffs. We show how data mining in blockchain data could be incorporated into a heuristic model which provides parameters for the game-theoretic payoff matrix. Thus, this work represents a platform for simulating the evolutionary dynamics of the agents' behaviors, including also heuristics and homophily on a multi-layer blockchain network.","PeriodicalId":240048,"journal":{"name":"Proceedings of the 21st International Conference on Distributed Computing and Networking","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133616044","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}

{"title":"Study on Phytoplankton variability of Sundarban Estuarine river using Random Forests Classifier","authors":"S. Chakraborti, G. Sen, Joydeep Mekherjee","doi":"10.1145/3369740.3372761","DOIUrl":"https://doi.org/10.1145/3369740.3372761","url":null,"abstract":"Statistical Classifier Random Forests (RF) is nowadays extensively used by ecologists for accurate classification, determination of variable importance, understanding of complex interactions in ecosystem studies. In the present study, extensive observation data collected from a river of SES, Sundarban Estuarine System (River Jagaddal, situated in the southernmost part of western Sundarbans and in the closed proximity to Northern boundary of Bay of Bengal) has been used to perform rigorous data analysis using Random Forests. The basic objective of the study is to identify variability, importance and associated interactions for phytoplankton as well as chlorophyll concentrations along the river stretch. This study enables us to identify status of productivity pertinent to availability as well as growth of fish production of this region. It may be noted that most of the people residing in these areas have sole dependency of earning from fishing. RF model has a high predictive power. The interpretations of RF model can be visualized by feature importance graphs which evaluate a feature as a whole which means, contribution of all the properties to a certain phenomena can be observed. In this approach, Random Forest (RF) classification algorithm has been used to classify different properties of estuarine water according to their individual roles on the phytoplankton density and chlorophyll-a concentrations. The properties are classified as significant, moderately significant and insignificant on the basis of their roles (as obtained from RF model) in modulating phytoplankton density and chlorophyll-a concentration. The present study reveals that the phytoplankton density is strongly influenced by the distance from the sea. Surface salinity is the other important factor to be considered as per our findings. Surface phosphate and surface nitrate are marked to be the other important dominating factors on phytoplankton density. In fact, nitrogen and phosphorus are the primary factors that control phytoplankton abundance in estuaries. The bottom temperature has little significance on phytoplankton density as per model investigation. But, the roles of the other factors like surface temperature (st), bottom phosphate (bp) and bottom salinity (bs) have found to be literally insignificant. The chlorophyll-a concentrations found in the study area during study period are found to be strongly correlated to phytoplankton density. This is quite expected since chlorophyll-a concentration can be used as a direct measure of phytoplankton density. The surface phosphate and bottom salinity also observed to have significant influences on chlorophyll-a concentration. It can also be concluded from the model output that, surface phosphate is the most important limiting nutrient on the chlorophyll-a concentration in this specific study area. Usually, there is a general consensus that there are seasonal and spatial variations of the limiting nutrients which in turn are the mos","PeriodicalId":240048,"journal":{"name":"Proceedings of the 21st International Conference on Distributed Computing and Networking","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128281590","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}