scholarly journals Optimizing Reachability Sets in Temporal Graphs by Delaying

2020 ◽  
Vol 34 (06) ◽  
pp. 9810-9817
Author(s):  
Argyrios Deligkas ◽  
Igor Potapov
Keyword(s):  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Control Mechanisms ◽  
Scheduling Problems ◽  
Dynamic Graph ◽  
Time Step ◽  
Supply Networks ◽  
Reachability Sets ◽  
Network Epidemiology ◽  
Temporal Graphs

A temporal graph is a dynamic graph where every edge is assigned a set of integer time labels that indicate at which discrete time step the edge is available. In this paper, we study how changes of the time labels, corresponding to delays on the availability of the edges, affect the reachability sets from given sources. The questions about reachability sets are motivated by numerous applications of temporal graphs in network epidemiology and scheduling problems in supply networks in manufacturing. We introduce control mechanisms for reachability sets that are based on two natural operations of delaying time events. The first operation, termed merging, is global and batches together consecutive time labels in the whole network simultaneously. This corresponds to postponing all events until a particular time. The second, imposes independent delays on the time labels of every edge of the graph. We provide a thorough investigation of the computational complexity of different objectives related to reachability sets when these operations are used. For the merging operation, we prove NP-hardness results for several minimization and maximization reachability objectives, even for very simple graph structures. For the second operation, we prove that the minimization problems are NP-hard when the number of allowed delays is bounded. We complement this with a polynomial-time algorithm for the case of unbounded delays.

scholarly journals Single-Machine Scheduling with Rejection and an Operator Non-Availability Interval

Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 668 ◽  
Author(s):  
Lili Zuo ◽  
Zhenxia Sun ◽  
Lingfa Lu ◽  
Liqi Zhang
Keyword(s):  
Polynomial Time ◽  
Single Machine ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Single Machine Scheduling ◽  
Total Weighted Completion Time ◽  
Scheduling Problems ◽  
Objective Functions ◽  
Rejection Cost ◽  
Scheduling With Rejection

In this paper, we study two scheduling problems on a single machine with rejection and an operator non-availability interval. In the operator non-availability interval, no job can be started or be completed. However, a crossover job is allowed such that it can be started before this interval and completed after this interval. Furthermore, we also assume that job rejection is allowed. That is, each job is either accepted and processed in-house, or is rejected by paying a rejection cost. Our task is to minimize the sum of the makespan (or the total weighted completion time) of accepted jobs and the total rejection cost of rejected jobs. For two scheduling problems with different objective functions, by borrowing the previous algorithms in the literature, we propose a pseudo-polynomial-time algorithm and a fully polynomial-time approximation scheme (FPTAS), respectively.

scholarly journals A Blockchain-Based Multi-Factor Authentication Model for Cloud-Enabled Internet of Vehicles

2021 ◽  
Author(s):  
Victor R. Kebande ◽  
Feras Awaysheh ◽  
Richard Ikuesan ◽  
Sadi Alawadi ◽  
Mohammad Alshehri
Keyword(s):  
Vehicular Networks ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Control Mechanisms ◽  
Internet Of Vehicles ◽  
Single Sign On ◽  
Information And Communication ◽  
Adversarial Model ◽  
Cloud Applications ◽  
Probabilistic Polynomial Time

Continuous and emerging advances in Information and Communication Technology (ICT) have enabled IoT-to-Cloud applications to be induced by data pipelines coupled with Edge Intelligence-based architectures. Advanced vehicular networks greatly benefit from these architectures due to the implicit functionalities that are focused on realizing the Internet-of-Vehicle (IoV) vision. However, IoV is susceptible to attacks, where adversaries can easily exploit existing vulnerabilities. Several attacks may succeed due to inadequate or weaker authentication techniques. Hence, there is a timely need for hardening the authentication process through cutting-edge access control mechanisms. This paper proposes a Blockchain-based Multi-Factor authentication model that uses an embedded Digital Signature (MFBC_eDS) for vehicular clouds and Cloud-enabled IoV. Our proposed MFBC_eDS model consists of a scheme that integrates the Security Assertion Mark-up Language (SAML) to the Single Sign-On (SSO) capabilities for a connected Edge-to Cloud ecosystem. MFBC_eDS draws an essential comparison with the baseline authentication scheme suggested by Karla and Sood. Based on the foundations of Karla and Sood’s scheme, an embedded Probabilistic Polynomial-Time Algorithm (ePPTA) and an additional Hash function for the Pi generated during Karla and Sood’s authentication are proposed and discussed. The preliminary analysis of the proposition shows that the approach is more suitable to counter major adversarial attacks in an IoV-centered environment based on Dolev-Yao adversarial model while satisfying aspects of the CIA triad.

OPTIMIZING DATA THROUGHPUT IN CLIENT/SERVER SYSTEMS BY KEEPING QUEUE SIZES BALANCED

2012 ◽  
Vol 04 (02) ◽  
pp. 1250040
Author(s):  
E. KRANAKIS ◽  
D. KRIZANC ◽  
I. LAMBADARIS ◽  
L. NARAYANAN ◽  
J. OPATRNY
Keyword(s):  
Data Gathering ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Base Stations ◽  
Single Server ◽  
Wireless Devices ◽  
Time Step ◽  
Data Throughput ◽  
Server Systems ◽  
Overall Performance

Consider a synchronous system of clients and servers whereby client requests may be satisfied by any one of the servers the clients are assigned to and where the association between clients and servers is determined by an arbitrary but predefined apportionment of the set of servers to clients and of clients to servers. A client can get the required service from any of the servers it is assigned to and at each time step all clients make a request to the servers which then provide the service according to requests. Since clients can make requests simultaneously, if there is no coordination in the "client-to-server" assignment process some clients may have to wait longer if they are assigned simultaneously to a single server when overall performance could improve had they been assigned to separate available servers. Therefore a principal approach to optimizing throughput when assigning client requests to supporting servers, is to keep the client queue sizes well balanced so as to prevent servers from having to remain idle while other servers are being overused. There are several potential examples of such systems involving data gathering and forwarding among sensors in a sensor network or when the servers are base-stations and the clients may be either rotating satellites or other wireless devices, for example. In this paper we consider the problem of finding an assignment of clients to servers that results in all clients receiving a packet while optimally balancing the sizes of remaining queues at the clients. We give a polynomial time algorithm for solving this problem which requires O((m + n)3n) arithmetic operations, where m is the number of client queues and n is the number of servers.

scholarly journals Optimal algorithms for scheduling under time-of-use tariffs

2021 ◽  
Author(s):  
Lin Chen ◽  
Nicole Megow ◽  
Roman Rischke ◽  
Leen Stougie ◽  
José Verschae
Keyword(s):  
Polynomial Time ◽  
Single Machine ◽  
Completion Time ◽  
Optimal Algorithm ◽  
Optimal Schedule ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Single Machine Scheduling ◽  
Total Weighted Completion Time ◽  
Scheduling Problems

AbstractWe consider a natural generalization of classical scheduling problems to a setting in which using a time unit for processing a job causes some time-dependent cost, the time-of-use tariff, which must be paid in addition to the standard scheduling cost. We focus on preemptive single-machine scheduling and two classical scheduling cost functions, the sum of (weighted) completion times and the maximum completion time, that is, the makespan. While these problems are easy to solve in the classical scheduling setting, they are considerably more complex when time-of-use tariffs must be considered. We contribute optimal polynomial-time algorithms and best possible approximation algorithms. For the problem of minimizing the total (weighted) completion time on a single machine, we present a polynomial-time algorithm that computes for any given sequence of jobs an optimal schedule, i.e., the optimal set of time slots to be used for preemptively scheduling jobs according to the given sequence. This result is based on dynamic programming using a subtle analysis of the structure of optimal solutions and a potential function argument. With this algorithm, we solve the unweighted problem optimally in polynomial time. For the more general problem, in which jobs may have individual weights, we develop a polynomial-time approximation scheme (PTAS) based on a dual scheduling approach introduced for scheduling on a machine of varying speed. As the weighted problem is strongly NP-hard, our PTAS is the best possible approximation we can hope for. For preemptive scheduling to minimize the makespan, we show that there is a comparably simple optimal algorithm with polynomial running time. This is true even in a certain generalized model with unrelated machines.

scholarly journals Two-Agent Preemptive Pareto-Scheduling to Minimize Late Work and Other Criteria

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1517
Author(s):  
Ruyan He ◽  
Jinjiang Yuan
Keyword(s):  
Objective Function ◽  
Polynomial Time ◽  
Single Machine ◽  
Completion Time ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Pareto Optimal ◽  
Scheduling Problems ◽  
Trade Off ◽  
Late Work

In this paper, we consider three preemptive Pareto-scheduling problems with two competing agents on a single machine. In each problem, the objective function of agent A is the total completion time, the maximum lateness, or the total late work while the objective function of agent B is the total late work. For each problem, we provide a polynomial-time algorithm to characterize the trade-off curve of all Pareto-optimal points.

scholarly journals A Blockchain-Based Multi-Factor Authentication Model for a Cloud-Enabled Internet of Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6018
Author(s):  
Victor R. Kebande ◽  
Feras M. Awaysheh ◽  
Richard A. Ikuesan ◽  
Sadi A. Alawadi ◽  
Mohammad Dahman Alshehri
Keyword(s):  
Vehicular Networks ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Control Mechanisms ◽  
Internet Of Vehicles ◽  
Single Sign On ◽  
Information And Communication ◽  
Adversarial Model ◽  
Cloud Applications ◽  
Probabilistic Polynomial Time

Continuous and emerging advances in Information and Communication Technology (ICT) have enabled Internet-of-Things (IoT)-to-Cloud applications to be induced by data pipelines and Edge Intelligence-based architectures. Advanced vehicular networks greatly benefit from these architectures due to the implicit functionalities that are focused on realizing the Internet of Vehicle (IoV) vision. However, IoV is susceptible to attacks, where adversaries can easily exploit existing vulnerabilities. Several attacks may succeed due to inadequate or ineffective authentication techniques. Hence, there is a timely need for hardening the authentication process through cutting-edge access control mechanisms. This paper proposes a Blockchain-based Multi-Factor authentication model that uses an embedded Digital Signature (MFBC_eDS) for vehicular clouds and Cloud-enabled IoV. Our proposed MFBC_eDS model consists of a scheme that integrates the Security Assertion Mark-up Language (SAML) to the Single Sign-On (SSO) capabilities for a connected edge to cloud ecosystem. MFBC_eDS draws an essential comparison with the baseline authentication scheme suggested by Karla and Sood. Based on the foundations of Karla and Sood’s scheme, an embedded Probabilistic Polynomial-Time Algorithm (ePPTA) and an additional Hash function for the Pi generated during Karla and Sood’s authentication were proposed and discussed. The preliminary analysis of the proposition shows that the approach is more suitable to counter major adversarial attacks in an IoV-centered environment based on the Dolev–Yao adversarial model while satisfying aspects of the Confidentiality, Integrity, and Availability (CIA) triad.

scholarly journals Single-Machine Scheduling with Learning Effects and Maintenance: A Methodological Note on Some Polynomial-Time Solvable Cases

2017 ◽  
Vol 2017 ◽  
pp. 1-6
Author(s):  
Kuo-Ching Ying ◽  
Chung-Cheng Lu ◽  
Shih-Wei Lin ◽  
Jie-Ning Chen
Keyword(s):  
Polynomial Time ◽  
Single Machine ◽  
Machine Scheduling ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Single Machine Scheduling ◽  
Learning Effects ◽  
Scheduling Problems ◽  
Maintenance Activity ◽  
Processing Times

This work addresses four single-machine scheduling problems (SMSPs) with learning effects and variable maintenance activity. The processing times of the jobs are simultaneously determined by a decreasing function of their corresponding scheduled positions and the sum of the processing times of the already processed jobs. Maintenance activity must start before a deadline and its duration increases with the starting time of the maintenance activity. This work proposes a polynomial-time algorithm for optimally solving two SMSPs to minimize the total completion time and the total tardiness with a common due date.

scholarly journals Scheduling Jobs with Variable Job Processing Times on Unrelated Parallel Machines

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Guang-Qian Zhang ◽  
Jian-Jun Wang ◽  
Ya-Jing Liu
Keyword(s):  
Resource Allocation ◽  
Parallel Machines ◽  
Waiting Times ◽  
Optimal Schedule ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Unrelated Parallel Machines ◽  
Scheduling Problems ◽  
Processing Times ◽  
Parallel Machines Scheduling

munrelated parallel machines scheduling problems with variable job processing times are considered, where the processing time of a job is a function of its position in a sequence, its starting time, and its resource allocation. The objective is to determine the optimal resource allocation and the optimal schedule to minimize a total cost function that dependents on the total completion (waiting) time, the total machine load, the total absolute differences in completion (waiting) times on all machines, and total resource cost. If the number of machines is a given constant number, we propose a polynomial time algorithm to solve the problem.

Learning Importance of Preferences

10.29007/v68w ◽  
2018 ◽  
Author(s):  
Ying Zhu ◽  
Mirek Truszczynski
Keyword(s):  
Polynomial Time ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Scoring Rules ◽  
Np Hard ◽  
Individual Preferences

We study the problem of learning the importance of preferences in preference profiles in two important cases: when individual preferences are aggregated by the ranked Pareto rule, and when they are aggregated by positional scoring rules. For the ranked Pareto rule, we provide a polynomial-time algorithm that finds a ranking of preferences such that the ranked profile correctly decides all the examples, whenever such a ranking exists. We also show that the problem to learn a ranking maximizing the number of correctly decided examples (also under the ranked Pareto rule) is NP-hard. We obtain similar results for the case of weighted profiles when positional scoring rules are used for aggregation.

scholarly journals Metric Dimension Parameterized By Treewidth

Algorithmica ◽  
2021 ◽  
Author(s):  
Édouard Bonnet ◽  
Nidhi Purohit
Keyword(s):  
Computable Function ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Minimum Size ◽  
Metric Dimension ◽  
Resolving Set ◽  
Input Graph ◽  
Outerplanar Graphs ◽  
Bounded Treewidth ◽  
Fpt Algorithm

AbstractA resolving set S of a graph G is a subset of its vertices such that no two vertices of G have the same distance vector to S. The Metric Dimension problem asks for a resolving set of minimum size, and in its decision form, a resolving set of size at most some specified integer. This problem is NP-complete, and remains so in very restricted classes of graphs. It is also W[2]-complete with respect to the size of the solution. Metric Dimension has proven elusive on graphs of bounded treewidth. On the algorithmic side, a polynomial time algorithm is known for trees, and even for outerplanar graphs, but the general case of treewidth at most two is open. On the complexity side, no parameterized hardness is known. This has led several papers on the topic to ask for the parameterized complexity of Metric Dimension with respect to treewidth. We provide a first answer to the question. We show that Metric Dimension parameterized by the treewidth of the input graph is W[1]-hard. More refinedly we prove that, unless the Exponential Time Hypothesis fails, there is no algorithm solving Metric Dimension in time $$f(\text {pw})n^{o(\text {pw})}$$ f ( pw ) n o ( pw ) on n-vertex graphs of constant degree, with $$\text {pw}$$ pw the pathwidth of the input graph, and f any computable function. This is in stark contrast with an FPT algorithm of Belmonte et al. (SIAM J Discrete Math 31(2):1217–1243, 2017) with respect to the combined parameter $$\text {tl}+\Delta$$ tl + Δ , where $$\text {tl}$$ tl is the tree-length and $$\Delta$$ Δ the maximum-degree of the input graph.

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