Broadcast Problem Research Articles

Smoothed Analysis of Information Spreading in Dynamic Networks

The best known solutions for k -message broadcast in dynamic networks of size n require Ω ( nk ) rounds. In this article, we see if these bounds can be improved by smoothed analysis. To do so, we study perhaps the most natural randomized algorithm for disseminating tokens in this setting: at every timestep, choose a token to broadcast randomly from the set of tokens you know. We show that with even a small amount of smoothing (i.e., one random edge added per round), this natural strategy solves k -message broadcast in \(\tilde{O}(n+k^3)\) rounds, with high probability, beating the best known bounds for \(k=o(\sqrt {n})\) and matching the Ω ( n + k ) lower bound for static networks for k = O ( n 1/3 ) (ignoring logarithmic factors). In fact, the main result we show is even stronger and more general: Given ℓ-smoothing (i.e., ℓ random edges added per round), this simple strategy terminates in \(O(kn^{2/3}\log ^{1/3}(n)\ell ^{-1/3})\) rounds. We then prove this analysis close to tight with an almost-matching lower bound. To better understand the impact of smoothing on information spreading, we next turn our attention to static networks, proving a tight bound of \(\tilde{O}(k\sqrt {n})\) rounds to solve k -message broadcast, which is better than what our strategy can achieve in the dynamic setting. This confirms the intuition that although smoothed analysis reduces the difficulties induced by changing graph structures, it does not eliminate them altogether. Finally, we apply tools developed to support our smoothed analysis to prove an optimal result for k -message broadcast in so-called well-mixed networks in the absence of smoothing. By comparing this result to an existing lower bound for well-mixed networks, we establish a formal separation between oblivious and strongly adaptive adversaries with respect to well-mixed token spreading, partially resolving an open question on the impact of adversary strength on the k -message broadcast problem.

Parameterized complexity of broadcasting in graphs

The task of the broadcast problem is, given a graph G and a source vertex s, to compute the minimum number of rounds required to disseminate a piece of information from s to all vertices in the graph. It is assumed that, at each round, an informed vertex can transmit the information to at most one of its neighbors. The broadcast problem is known to NP-hard. We show that the problem is FPT when parametrized by the size k of a feedback edge set, or by the size k of a vertex cover, or by k=n−t, where t is the input deadline for the broadcast protocol to complete.

Data Aggregation through Hybrid Optimal Probability in Wireless Sensor Networks


 INTRODUCTION: In the realm of Wireless Sensor Networks (WSN), effective data dissemination is vital for applications like traffic alerts, necessitating innovative solutions to tackle challenges such as broadcast storms.
 OBJECTIVES: This paper proposes a pioneering framework that leverages probabilistic data aggregation to optimize communication efficiency and minimize redundancy.
 METHODS: The proposed adaptable system extracts valuable insights from the knowledge base, enabling dynamic route adjustments based on application-specific criteria. Through simulations addressing bandwidth limitations and local broadcast issues, we establish a robust WSN-based traffic information system.
 RESULTS: By employing primal-dual decomposition, the proposed approach identifies optimal packet aggregation probabilities and durations, resulting in reduced energy consumption while meeting latency requirements.
 CONCLUSION: The efficacy of proposed method is demonstrated across various traffic and topology scenarios, affirming that probabilistic data aggregation effectively mitigates the local broadcast problem, ultimately leading to decreased bandwidth demands.

Challenges and the Impact on the Performance of Ghanaian Universities’ Radio Broadcasting, the Case of Radio Universe 105.7fm.

The study sought to evaluate the challenges and effects of radio broadcasting at Ghanaian universities, with a special focus on Radio Universe 105.7FM. The study was conducted to get a knowledge of the issues connected with campus radio broadcasting, the impact of these challenges, and solutions to manage campus radio broadcasting. To achieve the study aims, a mixed research approach and an exploratory research design were used. The study made use of both primary and secondary data sources. The study included fourteen (14) people. To collect data from study participants, the researchers employed a self-administered questionnaire and an interview. Radio Universe operations are hampered, according to the study, by a lack of funds to run campus radio broadcasting, radio licensing and renewal requirements, businesses' unwillingness to place radio commercials on campus radio, infrastructure, equipment, logistics, and operations financing, particularly programming expenditures. The survey also discovered that campus radio station operations encounter difficulties in self-promotion and gaining the requisite personal knowledge to fulfill all commitments. The paper claims that radio operations fall short of society's expectations due to a lack of components judged appropriate for inclusion in public radio programs, which university radio cannot achieve. Managing campus radio operations, according to the research, needs proactive planning, sticking to a specific broadcasting goal, and hiring devoted workers. According to the report, Radio Universe may be managed by maintaining adequate logistics, awarding performance, establishing flexible work schedules, and rewarding stipends to student workers. As a non-profit organization, the report advised that Radio Universe's management seek financial assistance from Non- Governmental Organizations and the government. According to the findings, Radio Universe's human resource managers and leadership should improve their marketing strategies to acquire business patronage for their services. According to the findings, Radio Universe's operations are regularly updated to meet or anticipate the needs of their clientele. According to the report, Radio Universe should consider collaborating with other wellknown radio stations to address the challenges they face in their operations. The paper adds to the body of knowledge on campus radio broadcasting. The research also adds to the body of knowledge about the difficulties associated with campus radio broadcasting. The study also adds to the literature on the influence of radio broadcasting problems on radio station operations.

Asynchronous Byzantine reliable broadcast with a message adversary

This paper considers the problem of reliable broadcast in asynchronous authenticated systems, in which n processes communicate using signed messages and up to t processes may behave arbitrarily (Byzantine processes). In addition, for each message m broadcast by a correct (i.e., non-Byzantine) process, a message adversary may prevent up to d correct processes from receiving m. (This message adversary captures network failures such as transient disconnections, silent churn, or message losses.) Considering such a “double” adversarial context and assuming n>3t+2d, a reliable broadcast algorithm is presented. Interestingly, when there is no message adversary (i.e., d=0), the algorithm terminates in two communication steps (so, in this case, this algorithm is optimal in terms of both Byzantine tolerance and time efficiency). It is then shown that the condition n>3t+2d is necessary for implementing reliable broadcast in the presence of both Byzantine processes and a message adversary (whether the underlying system is enriched with signatures or not).

Distributed Stable Multisource Global Broadcast for SINR-Based Wireless Multihop Networks

Multi-source global broadcast is a fundamental problem in multi-hop wireless networks. The Static Multi-source Global Broadcast problem (SMGB), which considers static packet injection at all source nodes, has been extensively studied in recent years. However, packets are more likely to be continuously injected over time in realistic multi-hop wireless networks. In this paper, we focus on studying the Dynamic Multi-source Global Broadcast problem (DMGB), in which packets are continuously injected to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k\geq 2$ </tex-math></inline-formula> ) source nodes in the network according to a widely-used dynamic packet injection model and the objective is to disseminate each injected packet across the whole network quickly. We solve this DMGB problem under the Signal-to-Interference-plus-Noise-Ratio (SINR) interference model. Specifically, we first present a distributed randomized algorithm for solving the SMGB problem. We then iterate this SMGB algorithm repeatedly to construct a distributed DMGB algorithm. We prove the proposed DMGB algorithm is stable, i.e., the expected number of packets in each node’s message queue is bounded at any time and further the expected global broadcast latency for each injected packet is bounded. Simulation results validate the effectiveness of the proposed DMGB algorithm.

Research on the Influence of Promotion Types and Scarcity on Consumers' Purchase Intention in The Context of E-commerce Live Broadcasting

E-commerce live broadcasting has become a popular form of e-commerce sales. Compared with traditional marketing channels, e-commerce live broadcasting can more influence consumers' purchasing behavior. Based on relevant theories such as frame effect theory, commodity theory and scarcity effect, and combined with practical marketing problems of e-commerce live broadcasting, this paper discusses the influence of scarcity on consumers' purchase intention under different promotion methods in the context of e-commerce live broadcasting, as well as its internal mechanism. In this paper, we publish online questionnaires on the data platform to collect the required data. SPSS and AMOS software are used as analysis tools to analyze the collected data. The results of experiment 1 show that when anchors use price discount promotion in live broadcast, compared with limited time, the use of quantity limited can stimulate consumers to have higher purchase intention. When the host adopts the gift promotion method, compared with the quantity limited, the use of limited time can better stimulate consumers' purchase intention. The results of experiment 2 show that, when price discount promotion is adopted, perceived value plays an intermediary role in the influence of quantity limited on consumers' purchase intention, discount range plays a moderating role in the relationship between quantity limited and purchase intention, and discount range can effectively regulate the relationship between quantity limited and purchase intention through the intermediary of perceived value. The results of experiment 3 show that when the gift promotion method is adopted, perceptual arousal plays an intermediary role in the influence of time limit on consumers' purchase intention, and the gift correlation plays a moderating role in the relationship between time limit and purchase intention.

Mobility-aware coded caching in D2D communication networks

In this paper, we consider a cache-enable device-to-device (D2D) communication network with user mobility and design a mobility-aware coded caching scheme to exploit multicasting opportunities for reducing network traffic. In addition to the static cache memory that can be used to reap coded caching gains, we assign a dynamic cache memory to mobile users such that users who never meet can still exchange contents via relaying. We consider content exchange as an information flow among dynamic cache memories of mobile users and leverage network coding to reduce network traffic. Specifically, we transfer our storage and broadcast problem into a network coding problem. By solving the formulated network coding problem, we obtain a dynamic content replacement and broadcast strategy. Numerical results verify that our algorithm significantly outperforms the random and greedy algorithms in terms of the amount of broadcasting data, and the standard Ford–Fulkerson algorithm in terms of the successful decoding ratio.

An analysis of probabilistic forwarding of coded packets on random geometric graphs

We consider the problem of energy-efficient broadcasting on large ad-hoc networks. Ad-hoc networks are generally modelled using random geometric graphs (RGGs). Here, nodes are deployed uniformly in a square area around the origin, and any two nodes which are within Euclidean distance of 1 are assumed to be able to receive each other’s broadcast. A source node at the origin encodes k data packets of information into n(>k) coded packets and transmits them to all its one-hop neighbours. The encoding is such that, any node that receives at least k out of the n coded packets can retrieve the original k data packets. Every other node in the network follows a probabilistic forwarding protocol; upon reception of a previously unreceived packet, the node forwards it with probability p and does nothing with probability 1−p. We are interested in the minimum forwarding probability which ensures that a large fraction of nodes can decode the information from the source. We deem this a near-broadcast. The performance metric of interest is the expected total number of transmissions at this minimum forwarding probability, where the expectation is over both the forwarding protocol as well as the realization of the RGG. In comparison to probabilistic forwarding with no coding, our treatment of the problem indicates that, with a judicious choice of n, it is possible to reduce the expected total number of transmissions while ensuring a near-broadcast.

THE FORMATION OF ECOLOGICAL CULTURE OF CHILDREN THROUGH THE PERFORMANCE "ADVENTURE OF THE SNOW LEOPARD" OF THEATER FOR CHILDREN AND YOUTH NAMED AFTER N. SATS

The article considers the possibility of forming the ecological culture of the younger generation through theatrical art, where the fairy tale is the main pedagogical technique of environmental education of students. Currently, along with the traditional genres of TYUZ (magic, social and household fairy tales, children's musical, etc.), the range of children's drama is expanding due to the integration of modern stage forms into the TYUZ repertoire, such as plastic drama, ecological theater, children's performance, etc. The maximum adaptability of the language of performance to children's emotional perception (stage entertainment and dynamics), the use of advanced technologies in the theatrical production industry and the danger of a potential environmental catastrophe justify the relevance of the functioning of the ecotheater for changing children's psychology and awareness of priority environmental values. The purpose of ecological productions of the world children's theater, including in Kazakhstan, is to form the correct children's ecological worldview, to foster a sense of responsibility to the living and inanimate nature, civic duty and national patriotism. The study of the problem of environmental education of children through theatrical art on the example of the play "The Adventure of the Snow Leopard" of the Theater for Children and Youth named after N. Sats allowed to identify the solution of a number of eco-pedagogical tasks of the state noted in the Message of the President of the Republic of Kazakhstan. The research results obtained during the survey diagnose the relevance of an unconventional artistic approach through the visualization of a broadcast problem in the issues of environmental education of students.

The impact of channel model on the performance of distance-based schemes in vehicular named data networks

&lt;span lang="EN-US"&gt;Distance-based schemes present one of the methods to avoid the broadcast problem in vehicular named data networks. However, such schemes overlook the most factor in performance evaluation which is the variation in received signal strength caused by the propagation model choice. Thus, they are evaluated under one propagation model while neglecting the effect of the others. This paper evaluates the impact of the propagation variation model over three distance-based schemes, namely rapid named data networking (RNDN), enhanced vehicle on named data networking (EVNDN) and opportunistic interest forwarding protocol (OIFP). Simulation experiments are performed over three propagation models. Simulation results show that Nakagami significantly degrades network performance. However, it has a noticeable positive effect over higher distance resulting in a higher interest satisfaction ratio as compared to the other models. The RNDN exhibits a higher number of retransmissions across the Nakagami. In contrast, a higher number of retransmissions is exhibited by EVNDN when compared to the other schemes over the Friis and random. The OIFP show a higher interest satisfaction ratio when compared to EVNDN and RNDN under all models. OIFP shows robustness towards the adverse fading effects resulting from the Nakagami and exhibits lower end to end delays.&lt;/span&gt;

Efficient and competitive broadcast in multi-channel radio networks

Consider a single-hop, multi-channel, synchronous radio network in which a source node needs to disseminate a message to all other n−1 nodes. An adversary called Eve, which captures environmental noise and potentially malicious interference, aims to disrupt this process via jamming. Assume sending, listening, or jamming on one channel for one time slot costs one unit of energy. The question is, if Eve spends T units of energy on jamming, can we devise broadcast algorithms in which each node's cost is o(T)? Previous results show such resource competitive algorithms do exist in the single-channel setting: for large T values, each node can receive the message within O(T) time slots while spending only O˜(T/n) energy.In this work, we devise new broadcast algorithms and show that the existence of multiple channels allows faster message dissemination while preserving resource competitiveness. Specifically, if C channels are available, for large T values, our algorithms guarantee each node's runtime is O(T/C), and each node's energy cost is O˜(T/n). Moreover, our algorithms require minimal prior knowledge and allow Eve to be adaptive. Our technical contributions lie in using “epidemic broadcast” in algorithm design to achieve time efficiency and resource competitiveness, and employing coupling techniques in the analysis to handle the adaptivity of the adversary.We also complement algorithmic results with lower bounds, proving both the time complexity and the energy complexity of our algorithms are optimal or near-optimal. In particular, to obtain the lower bound on resource competitiveness, we first prove a new lower bound showing any multi-channel 1-to-1 communication algorithm succeeding with constant probability incurs expected cost of at least Ω(T); then, via simulation and reduction arguments, we show for the broadcast problem, some node incurs a cost of at least Ω(T/n), even in the multi-channel setting.

Throughput-Optimal Broadcast for Time-Varying Directed Acyclic Wireless Multi-Hop Networks With Energy Harvesting Constraints

In wireless multi-hop networks, a fundamental problem is to disseminate continuous data traffic from a source node to all other network nodes, which is known as the broadcast problem. Such a problem becomes even more complicated in wireless multi-hop networks with energy-harvesting capabilities at nodes when facing the interaction between stochastics of traffic arrivals at the source and randomness of energy-harvesting process at nodes. In such networks, the energy consumable at a node cannot exceed the amount of the energy harvested at the node. In this paper, we investigate the throughput-optimal broadcast problem in time-varying directed acyclic wireless multi-hop networks with such energy harvesting constraints. The topologies of such networks change dynamically with time while satisfying the directed acyclic property and the energy arrival time and harvested amount at a node are random, which causes the consumable energy in each time slot to fluctuate with time. Existing throughput-optimal broadcast algorithms did not consider such energy-harvesting constraints in their designs and therefore their throughput-optimal properties do not hold anymore in such a network. In this paper, we characterize the energy-harvesting uncertainties at nodes by using time-varying per-slot-based supportable transmission rates of wireless links. We consider the time-varying property of supportable link transmission rates caused by energy-harvesting dynamics in the per-slot transmission scheduling and propose an online max-weight broadcast algorithm. We derive a tight upper bound of broadcast capacity of the wireless networks under study in this paper and further prove that our proposed algorithm is throughput-optimal. We evaluate the throughput and latency performance of the proposed algorithm by simulations and the simulation results affirm our theoretical analysis.

Throughput-Optimal Dynamic Broadcast for SINR-Based Multi-Hop Wireless Networks With Time-Varying Topology

The problem of disseminating continuous data flow from a given source node to all other network nodes is known as the dynamic broadcast problem, which is also a fundamental problem in multi-hop wireless networks (e.g., wireless ad hoc and sensor networks). Due to link unreliability and node mobility, the topology of a network typically changes with time. Little work has been conducted to address the dynamic broadcast problem in time-varying wireless multi-hop networks, especially under the popular Signal-to-Interference-plus-Noise-Ratio (SINR) interference model. In this paper, we study the dynamic broadcast problem in SINR-based time-varying directed acyclic multi-hop wireless networks formed by point-to-point wireless links. We consider the SINR-based link transmission rate model involved in the slot-based link scheduling. We first prove a tight upper bound for the broadcast capacity of the multi-hop wireless networks under study. We then propose an online max-weight Throughput-Optimal Dynamic Broadcast algorithm (TODB) which performs link weight allocation, link scheduling, and data forwarding for each time slot according to the current network connectivity and data reception rates of nodes. We derive the throughput-optimality of the TODB algorithm by proving that the broadcast throughput of TODB can achieve the aforementioned upper bound of the broadcast capacity. We evaluate the performance of TODB in terms of throughput and latency via simulations and the results validate its effectiveness.

The Neighborhood Broadcast Problem in Wireless Ad Hoc Sensor Networks

The Neighborhood Broadcast Problem in Wireless Ad Hoc Sensor Networks

An Exact Implementation of the Abstract MAC Layer via Carrier Sensing in Dynamic Networks

In this paper, we present the first algorithm to precisely implement the abstract MAC (absMAC) layer under the physical SINR model in dynamic networks. The absMac layer, first presented by (Kuhn et al., 2009), provides reliable local broadcast communications, with timing guarantees stated in terms of a collection of abstract delay functions, based on which high-level algorithms can be designed, independent of specific channel behaviors. The implementation of absMAC requires the design of a distributed algorithm for the local broadcast communication primitives over a particular communication model that defines concrete channel behaviors, and the objective is to minimize the bounds of the abstract delay functions. Halldórsson et al. (2015) showed that under the standard SINR model (synchronous communications without physical carrier sensing or location information), there exist no efficient exact implementations. In this work, we demonstrate that physical carrier sensing, a commonly seen function performed by wireless devices, can help get efficient exact implementation algorithms. Specifically, we propose an algorithm that precisely implements the absMAC layer under the SINR model in dynamic networks. The algorithm provides asymptotically optimal bounds for both acknowledgement and progress functions defined in the absMAC layer. Our algorithm leads to many new faster algorithms for solving high-level problems under the SINR model in dynamic networks. We demonstrate this by exemplifying problems of Consensus, Multi-Message Broadcast, and Single-Message Broadcast. It deserves to point out that our implementation algorithm is designed based on an optimal algorithm for a General Local Broadcast (GLB) problem, which takes the number of distinct messages into consideration for the first time. The GLB algorithm can handle many communication scenarios apart from those defined in the absMAC layer. Simulation results show that our proposed algorithms perform well in reality.

Flower Pollination Algorithm with Powell’s Method for the Minimum Energy Broadcast Problem in Wireless Sensor Network

Minimum energy broadcast (MEB) problem in wireless sensor network has attracted attentions of the many researchers due to the limited bandwidth of the network and battery life of the sensor nodes. The data in a wireless network are transmitted from the source node to all other nodes and seek broadcast scheme to transmit with minimum energy consumption. The main objective of MEB is to minimize the transmission energy consumption of the network and is considered as an NP-complete problem. This work proposes a new variant of Flower pollination algorithm based on Powell’s method (PFPA) to solve MEB problem in wireless sensor networks. The proposed algorithm is compared with other heuristic approaches and the performance of the algorithm is assessed using benchmark instances with 50 and 100 nodes. The effectiveness and merit of the proposed algorithm is demonstrated in terms of performance metrics.

The Neighborhood Broadcast Problem in Wireless Ad Hoc Sensor Networks

The Neighborhood Broadcast Problem in Wireless Ad Hoc Sensor Networks

The Neighborhood Broadcast Problem in Wireless Ad Hoc Sensor Networks

The Neighborhood Broadcast Problem in Wireless Ad Hoc Sensor Networks

Distributed Stable Global Broadcasting for SINR-Based Multi-Channel Wireless Multi-Hop Networks

Recently, the problem of Stable Global Broadcasting (SGB) with continuous packet injections at a source node has attracted considerable attention and much work has been carried out. However, existing SGB algorithms are all centralized and under the graph-based interference model. How to achieve efficient distributed SGB under the more realistic Signal-to-Interference-plus-Noise-Ratio (SINR) interference model is still an open issue. In this paper, we focus on the design of distributed SGB algorithms for multi-channel wireless multi-hop networks under the SINR model. We first present an efficient Backbone-based Multi-channel Concurrent Scheduling (BMCS) strategy and prove an upper bound of $1/2$ packets/slot for the broadcast capacity (i.e., the maximum supportable packet injection rate for all possible SGB algorithms). By iterating the BMCS strategy in different ways, we present two distributed SGB algorithms, one for deterministic packet injection model corresponding to the broadcast capacity (called SGB-DPI) and another for stochastic packet injection model (called SGB-SPI). We prove that: 1) both SGB-DPI and SGB-SPI meet the queue stability and latency stability constraints for providing stable global broadcasting services, and 2) SGB-DPI is throughput-optimal. We evaluate the performance of our proposed algorithms through simulations. The simulation results validate our theoretical analysis and also show that even under the stochastic packet injection model, SGB-DPI has a comparable and even better throughput performance than SGB-SPI.