Helper Nodes Research Articles

Determinant Codes With Helper-Independent Repair for Single and Multiple Failures

Determinant codes are a class of exact-repair regenerating codes for distributed storage systems with parameters (n, k = d, d). These codes cover the entire trade-off between per-node storage and repair-bandwidth. In an earlier work of the authors, the repair data of the determinant code sent by a helper node to repair a failed node depends on the identity of the other helper nodes participating in the process, which is practically undesired. In this work, a new repair mechanism is proposed for determinant codes, which relaxes this dependency, while preserving all other properties of the code. Moreover, it is shown that the determinant codes are capable of repairing multiple failures, with a per-node repair-bandwidth which scales sub-linearly with the number of failures.

Energy Efficient Range-Free Localization Algorithm for Wireless Sensor Networks.

In this paper, an energy-efficient localization algorithm is proposed for precise localization in wireless sensor networks (WSNs) and the process is accomplished in three steps. Firstly, the beacon nodes discover their one-hop neighbor nodes with additional tone requests and reply packets over the media access control (MAC) layer to avoid collision of packets. Secondly, the discovered one-hop unknown nodes are divided into two sets, i.e. unknown nodes with direct communication, and with indirect communication for energy efficiency. In direct communication, source beacon nodes forward the information directly to the unknown nodes, but a common beacon node is selected for communication which reduces overall energy consumption during transmission in indirect communication. Finally, a correction factor is also introduced, and localized unknown nodes are upgraded into helper nodes for reducing the localization error. To analyze the efficiency and effectiveness of the proposed algorithm, various simulations are conducted and compared with the existing algorithms.

Centralized Multi-Node Repair Regenerating Codes

In a distributed storage system, recovering from multiple failures is a critical and frequent task that is crucial for maintaining the system's reliability and fault-tolerance. In this work, we focus on the problem of repairing multiple failures in a centralized way, which can be desirable in many data storage configurations, and we show that a significant repair traffic reduction is possible. First, the fundamental tradeoff between the repair bandwidth and the storage size for functional repair is established. Using a graph-theoretic formulation, the optimal tradeoff is identified as the solution to an integer optimization problem, for which a closed-form expression is derived. Expressions of the extreme points, namely the minimum storage multi-node repair (MSMR) and minimum bandwidth multi-node repair (MBMR) points, are obtained. Second, we describe a general framework for converting single erasure minimum storage regenerating codes to MSMR codes. The repair strategy for $e$ failures is similar to that for single failure, however certain extra requirements need to be satisfied by the repairing functions for single failure. For illustration, the framework is applied to product-matrix codes and interference alignment codes. Furthermore, we prove that the functional MBMR point is not achievable for linear exact repair codes. We also show that exact-repair minimum bandwidth cooperative repair (MBCR) codes achieve an interior point, that lies near the MBMR point, when $k \equiv 1 \mod e$, $k$ being the minimum number of nodes needed to reconstruct the entire data. Finally, for $k> 2e, e\mid k$ and $e \mid d$, where $d$ is the number of helper nodes during repair, we show that the functional repair tradeoff is not achievable under exact repair, except for maybe a small portion near the MSMR point, which parallels the results for single erasure repair by Shah et al.

OCA-MAC: A Cooperative TDMA-Based MAC Protocol for Vehicular Ad Hoc Networks.

Cooperative communication is an effective method of improving the transmission performance for vehicular ad hoc networks. However, the rapid movement of vehicles leads to frequent changes in network topology and reduces the probability of successful data transmission on the medium access control (MAC) layer. In this paper, we propose an Optimal Cooperative Ad hoc MAC protocol (OCA-MAC) based on time division multiple access (TDMA). OCA-MAC utilizes multiple cooperative nodes to forward data, so as to improve the probability of successful data transmission. It chooses cooperative nodes according to direct successful transmission probability, communication range between potential helper node and destination node, and available time slot. Meanwhile, in order to avoid excessive transmission redundancy caused by multiple cooperative forwarding, the optimal number of cooperative forwarding nodes is obtained through analysis of a probabilistic model. Simulation results show that OCA-MAC improves the successful data transmission rate and reduces the number of transmission times and transmission delay compared to the multichannel TDMA MAC protocol (VeMAC) and the cooperative ad hoc MAC protocol (CAH-MAC).

Joint Computation and Communication Cooperation for Energy-Efficient Mobile Edge Computing

This paper proposes a novel user cooperation approach in both computation and communication for mobile edge computing (MEC) systems to improve the energy efficiency for latency-constrained computation. We consider a basic three-node MEC system consisting of a user node, a helper node, and an access point (AP) node attached with an MEC server, in which the user has latency-constrained and computation-intensive tasks to be executed. We consider two different computation offloading models, namely, the partial and binary offloading, respectively. For partial offloading, the tasks at the user are divided into three parts that are executed at the user, helper, and AP, respectively; while for binary offloading, the tasks are executed as a whole only at one of three nodes. Under this setup, we focus on a particular time block and develop an efficient four-slot transmission protocol to enable the joint computation and communication cooperation . Besides the local task computing over the whole block, the user can offload some computation tasks to the helper in the first slot, and the helper cooperatively computes these tasks in the remaining time; while in the second and third slots, the helper works as a cooperative relay to help the user offload some other tasks to the AP for remote execution in the fourth slot. For both cases with partial and binary offloading, we jointly optimize the computation and communication resources allocation at both the user and the helper (i.e., the time and transmit power allocations for offloading, and the central process unit frequencies for computing), so as to minimize their total energy consumption while satisfying the user’s computation latency constraint. Although the two problems are nonconvex in general, we develop efficient algorithms to solve them optimally. Numerical results show that the proposed joint computation and communication cooperation approach significantly improves the computation capacity and energy efficiency at the user and helper, as compared to other benchmark schemes without such a joint design.

Minimizing the Adverse Effects of Asymmetric Links: A Novel Cooperative Asynchronous MAC Protocol for Wireless Sensor Networks.

As Wireless Sensor Networks (WSNs) grow in popularity, researchers are now focusing more on some challenging issues that significantly degrade overall performance, such as energy hole mitigation, link asymmetry minimization, etc. Link asymmetry is a problem that arises when the coverage distance between two adjacent nodes varies. It creates an obstacle to overcome when designing an efficient Medium Access Control (MAC) protocol for WSNs with low duty-cycling. This phenomenon poses an especially difficult challenge for receiver-initiated asynchronous MAC protocols, which are popular due to their relatively higher energy efficiency. Exploiting the benefits of cooperative communication has emerged as one of the viable solutions to overcome this limitation. Cooperative communication in WSNs has received a lot of attention in recent years. Many researchers have worked to create a MAC layer supporting cooperative communication. However, the association of cooperative communication with an asymmetric link is not studied in the literature. In this research work, COASYM-MAC, a cooperative asynchronous MAC protocol for WSNs, is proposed based on a receiver-initiated MAC protocol that uses the fact that nodes have alternate paths between them to reduce link asymmetry. A key feature of the proposed protocol is that the optimal helper node is selected automatically in case of link asymmetry. Simulations exhibited that COASYM-MAC performs significantly better than a state-of-the-art MAC protocol for WSNs that handles asymmetric links, ASYM-MAC.

Data offloading in cache-enabled cross-haul networks

This paper studies a cache-enabled cross-haul network (Ce-XHaul) infrastructure under the banner of 5G, aiming at offloading data requests in the backhaul networks by means of extremely restricting the provisioning of user requests in the fronthaul networks. The major motivation behind Ce-XHaul is to install a proper amount of cache storage in base stations (BSs) or in helper devices that are deployed between BSs and user devices (UEs), so as to store the frequently requested files from users, which sequentially reduce the requirement of access to the distant backhaul networks. Specifically, we first numerically study the network performance of Ce-XHaul in terms of latency, say the average transmission end-to-end (E2E) delay, under three network scenarios that differ with each other in the caching capabilities, named as no-caching (scenario 1), caching-at-BSs (scenario 2), and caching-at-helper nodes (scenario 3), respectively. Then, we dedicate on scenario 2 and investigate the impact of caching capability of BSs on the average transmission E2E delay by proposing two integer linear programming (ILP) models. The two ILP models are designed based on routing algorithms that differ in the efforts made to restrict the data provisioning in the fronthaul. Numerical results show that the more caching capability in the fronthaul, the less the latency, nonetheless, with higher CAPEX cost being induced due to deployment of the cache storage and the additional helper nodes.

Performance analysis of cache‐enabled wireless networks considering stochastic geometry approach

Caching of the popular content in the storages of local nodes near to the users has been proposed as a promising approach to handle the network data traffic and the backhaul constraint of access points in the cellular networks. These local storages, also called caches or helpers nodes, are the nodes with the limited communication range but with considerable storage capacities which are generally established condensed to realise the above goals. This dense distribution makes possible the collaboration among the helper nodes for exchanging their embedded files and delivery of the requested files to the users. In this study, to manage the traffic in smaller areas and also to establish more users' accesses to their requested files, clustered dense helper scenario is considered. More precisely, the helper nodes are grouped in disjoint clusters, through the clustering strategy induced by Matern hard core point process. Then the closed-form expressions based on stochastic geometry are derived for some performance metrics of the network. The analytical derivations are validated with Monte Carlo simulations which also compare two cases of clustered dense helper nodes and fewer helper nodes without clustering scenarios. The results show the advantage of the former from the outage probability perspective.

The Repair Problem for Reed–Solomon Codes: Optimal Repair of Single and Multiple Erasures With Almost Optimal Node Size

The repair problem in distributed storage addresses recovery of the data encoded using an erasure code, for instance, a Reed–Solomon (RS) code. We consider the problem of repairing a single node or multiple nodes in RS-coded storage systems using the smallest possible amount of inter-nodal communication. According to the cut-set bound, communication cost of repairing $h\geqslant 1$ failed nodes for an $(n,k=n-r)$ maximum distance separable (MDS) code using $d$ helper nodes is at least $dhl/(d+h-k)$ , where $l$ is the size of the node. Guruswami and Wootters (2016) initiated the study of efficient repair of RS codes, showing that they can be repaired using a smaller bandwidth than under the trivial approach. At the same time, their work as well as follow-up papers stopped short of constructing RS codes (or any scalar MDS codes) that meet the cut-set bound with equality. In this paper, we construct the families of RS codes that achieve the cut-set bound for repair of one or several nodes. In the single-node case, we present the RS codes of length $n$ over the field ${\mathbb F}_{q^{l}}, l=\exp ((1+o(1))n\log n)$ that meet the cut-set bound. We also prove an almost matching lower bound on $l$ , showing that super-exponential scaling is both necessary and sufficient for scalar MDS codes to achieve the cut-set bound using linear repair schemes. For the case of multiple nodes, we construct a family of RS codes that achieve the cut-set bound universally for the repair of any $h=1,2, {\dots },r$ failed nodes from any subset of $d$ helper nodes, $k\leqslant d\leqslant n-h$ . For a fixed number of parities $r$ , the node size of the constructed codes is close to the smallest possible node size for codes with such properties.

Bandwidth Adaptive & Error Resilient MBR Exact Repair Regenerating Codes

Regenerating codes are efficient methods for distributed storage in storage networks, where node failures are common. They guarantee low cost data reconstruction and repair through accessing only a predefined number of arbitrarily chosen storage nodes in the network. In this paper, we consider two simultaneous extensions to the original regenerating codes framework introduced by Dimakis et al. ; 1) both data reconstruction and repair are resilient to the presence of a certain number of erroneous nodes in the network and 2) the number of helper nodes in every repair is not fixed, but is a flexible parameter that can be selected during the run-time. We study the fundamental limits of required total repair bandwidth and provide an upper bound for the storage capacity of these codes under these assumptions. We then focus on the minimum repair bandwidth (MBR) case and derive the exact storage capacity by presenting explicit coding schemes with exact repair, which achieve the upper bound of the storage capacity in the considered setup. To this end, we first provide a more natural extension of the well-known product matrix (PM) MBR codes, modified to provide flexibility in choosing the number of helpers in each repair, and simultaneously be robust to erroneous nodes in the network. This is achieved by proving the non-singularity for a family of matrices in large enough finite fields. We next provide another extension of the PM codes, based on a novel repair scheme which enables flexibility in the number of helpers and robustness against erroneous nodes without any extra cost in field size compared with the original PM codes.

Analysis and Ideas for Improved Routing in MANET

Mobile Ad hoc NETwork is a collection of mobile nodes connected with each other without any centralized infrastructure support. In MANET, every node acts as a router, thereby forwards the packet to other nodes through the best route possible. The cooperation of all other nodes is very essential for a node to transfer data to its desired destination. Throughput is a major factor that determines the health of any network including MANET and there can be many reasons that can disrupt the throughput. In this paper we deal with two prime reasons that may reduce the throughput in a MANET. The first reason is that, if a node behaves selfishly and utilizes the path only for forwarding its own packet, then the packets from other nodes will be dropped and the throughput will gradually get reduced. The second reason for reduction in throughput is the phenomenon called fading, which causes signal attenuation. This phenomenon creates path loss temporarily, during which the packet loss increases and the throughput takes a major hit. Removing such nodes from the network on the basis of doubt about its packet forwarding nature and ability will eventually weaken the network strength. Neglecting the original best route will also reduce the quality of the network. Both the cases of selfishness and fading can be normalized by switching over to an alternate path and coming back to the same route after a short period of time. Thereby the quality as well as the quantity of nodes involved in the network can be maintained. In this paper we have also introduced an innovation called helper nodes which will also help in the formation of alternate path and will very well neutralize the ill effects caused due to selfishness and fading.

DOTS: Delay-Optimal Task Scheduling Among Voluntary Nodes in Fog Networks

Through offloading the computing tasks of the task nodes (TNs) to the fog nodes (FNs) located at the network edge, the fog network is expected to address the unacceptable processing delay and heavy link burden existed in current cloud-based networks. Unlike most existing researches based on the command-mode offloading and full capability report, this paper develops a general analytical model of the task scheduling among voluntary nodes (VNs) in fog networks, wherein the VNs voluntarily contribute their capabilities for serving their neighboring TNs. A novel delay-optimal task scheduling (DOTS) algorithm is proposed to obtain the delay-optimal offloading solution according to the reported capabilities of the VNs. Extensive simulations are carried out in a fog network, and the numerical results indicate that the proposed DOTS algorithm can effectively provide the optimal set of the helper nodes, subtask sizes, and the TN transmission power to minimize the overall task processing delay. Moreover, compared with the command-mode offloading, the voluntary-mode achieves more balanced offloading and a higher fairness level among the FNs.

MIMO Gaussian State-Dependent Channels with a State-Cognitive Helper.

We consider the problem of channel coding over multiterminal state-dependent channels in which neither transmitters nor receivers but only a helper node has a non-causal knowledge of the state. Such channel models arise in many emerging communication schemes. We start by investigating the parallel state-dependent channel with the same but differently scaled state corrupting the receivers. A cognitive helper knows the state in a non-causal manner and wishes to mitigate the interference that impacts the transmission between two transmit–receive pairs. Outer and inner bounds are derived. In our analysis, the channel parameters are partitioned into various cases, and segments on the capacity region boundary are characterized for each case. Furthermore, we show that for a particular set of channel parameters, the capacity region is entirely characterized. In the second part of this work, we address a similar scenario, but now each channel is corrupted by an independent state. We derive an inner bound using a coding scheme that integrates single-bin Gel’fand–Pinsker coding and Marton’s coding for the broadcast channel. We also derive an outer bound and further partition the channel parameters into several cases for which parts of the capacity region boundary are characterized.

Cooperative Repair: Constructions of Optimal MDS Codes for All Admissible Parameters

Two widely studied models of multiple-node repair in distributed storage systems are centralized repair and cooperative repair. The centralized model assumes that all the failed nodes are recreated in one location, while the cooperative one stipulates that the failed nodes may communicate but are distinct, and the amount of data exchanged between them is included in the repair bandwidth. As our first result, we prove a lower bound on the minimum bandwidth of cooperative repair. We also show that the cooperative model is stronger than the centralized one, in the sense that any maximum distance separable (MDS) code with optimal repair bandwidth under the former model also has optimal bandwidth under the latter one. These results were previously known under the additional “uniform download” assumption, which is removed in our proofs. As our main result, we give explicit constructions of MDS codes with optimal cooperative repair for all possible parameters. More precisely, given any n, k, h, d such that 2 ≤ h ≤ n- d ≤ n- k we construct (n, k) MDS codes over the field F of size |F| ≥ (d + 1 - k)n that can optimally repair any h erasures from any d helper nodes. The repair scheme of our codes involves two rounds of communication. In the first round, each failed node downloads information from the helper nodes, and in the second one, each failed node downloads additional information from the other failed nodes. This implies that our codes achieve the optimal repair bandwidth using the smallest possible number of rounds.

Probabilistic Caching Based on Maximum Distance Separable Code in a User-Centric Clustered Cache-Aided Wireless Network

We investigate how the maximum-distance separable (MDS) coding can be incorporated into probabilistic caching to utilize the limited storage space efficiently. In a user-centric clustered wireless network, each caching helper node probabilistically caches a segment of MDS coded sequence of each file. The segment size is optimized to maximize the cache hit probability or successful file retrieval probability. We reveal that the best way of storing files is determined by the condition whether the average amount of MDS coded information stored for the requested file within a user’s cluster exceeds the amount required for file retrieval or not. In terms of the cache hit probability maximization, if the condition is not fulfilled, it is proved that storing the complete file with a low probability is optimal. Otherwise, storing either a segment as small as possible with a high probability or a complete file with a low probability, according to a given environment, is shown to be desirable. We also analyze the successful retrieval probability, which accounts for both a cache hit event and successful transmissions from multiple caching helper nodes. Since the successful retrieval probability is in an intractable form, to find the desirable segment size, the theoretically driven algorithms with low search complexity are developed.

Capacity of Wireless Distributed Storage Systems With Broadcast Repair

In wireless distributed storage systems, storage nodes are connected by wireless channels, which are broadcast in nature. This paper exploits this unique feature to design an efficient repair mechanism, called broadcast repair, for wireless distributed storage systems in the presence of multiple-node failures. Due to the broadcast nature of wireless transmission, we advocate a new measure on repair performance called repair-transmission bandwidth. In contrast to repair bandwidth, which measures the average number of packets downloaded by a newcomer to replace a failed node, repair-transmission bandwidth measures the average number of packets transmitted by helper nodes per failed node. The storage system we considered can undergo an unlimited number of repair rounds. We obtain an upper bound on the maximum file size that can be supported by a cut analysis of a finite graph. The achievability is shown by codes constructed over a refined information flow graph, which is unbounded. In addition, the optimal storage-bandwidth tradeoff is obtained. The performance of broadcast repair is compared both analytically and numerically with that of cooperative repair, the basic repair method for wired distributed storage systems with multiple-node failures. While cooperative repair is based on the idea of allowing newcomers to exchange packets, broadcast repair is based on the idea of allowing a helper to broadcast packets to all newcomers simultaneously. We show that broadcast repair outperforms cooperative repair, offering a better tradeoff between storage efficiency and repair-transmission bandwidth.

MEETS: Maximal Energy Efficient Task Scheduling in Homogeneous Fog Networks

A homogeneous fog network is defined as a group of peer nodes with sharable computing and storage resources, as well as spare spectrum for node-to-node/device-to-device communications and task scheduling. It promotes more intelligent applications and services in different Internet of Things (IoT) scenarios, thanks to effective collaborations among neighboring fog nodes via cognitive spectrum access techniques. In this paper, a comprehensive analytical model that considers circuit, computation, offloading energy consumptions is developed for accurately evaluating the overall energy efficiency (EE) in homogeneous fog networks. With this model, the tradeoff relationship between performance gains and energy costs in collaborative task offloading is investigated, thus enabling us to formulate the EE optimization problem for future intelligent IoT applications with practical constraints in available computing resources at helper nodes and unused spectrum in neighboring environments. Based on rigorous mathematical analysis, a maximal energy-efficient task scheduling (MEETS) algorithm is proposed to derive the optimal scheduling decision for a task node and multiple neighboring helper nodes under feasible modulation schemes and time allocations. Extensive simulation results demonstrate the tradeoff relationship between EE and task scheduling performance in homogeneous fog networks. Compared with traditional task scheduling strategies, the proposed MEETS algorithm can achieve much better EE performance under different network parameters and service conditions.

Erasure coding for distributed storage: an overview

In a distributed storage system, code symbols are dispersed across space in nodes or storage units as opposed to time. In settings such as that of a large data center, an important consideration is the efficient repair of a failed node. Efficient repair calls for erasure codes that in the face of node failure, are efficient in terms of minimizing the amount of repair data transferred over the network, the amount of data accessed at a helper node as well as the number of helper nodes contacted. Coding theory has evolved to handle these challenges by introducing two new classes of erasure codes, namely regenerating codes and locally recoverable codes as well as by coming up with novel ways to repair the ubiquitous Reed-Solomon code. This survey provides an overview of the efforts in this direction that have taken place over the past decade.

The Storage Versus Repair-Bandwidth Trade-off for Clustered Storage Systems

We study a generalization of the setting of regenerating codes, motivated by applications to storage systems consisting of clusters of storage nodes. There are $n$ clusters in total, with $m$ nodes per cluster. A data file is coded and stored across the $mn$ nodes, with each node storing $\alpha$ symbols. For availability of data, we require that the file be retrievable by downloading the entire content from any subset of $k$ clusters. Nodes represent entities that can fail. We distinguish between intra-cluster and inter-cluster bandwidth (BW) costs during node repair. Node-repair in a cluster is accomplished by downloading $\beta$ symbols each from any set of $d$ other clusters, dubbed remote helper clusters, and also up to $\alpha$ symbols each from any set of $\ell$ surviving nodes, dubbed local helper nodes, in the host cluster. We first identify the optimal trade-off between storage-overhead and inter-cluster repair-bandwidth under functional repair, and also present optimal exact-repair code constructions for a class of parameters. The new trade-off is strictly better than what is achievable via space-sharing existing coding solutions, whenever $\ell > 0$. We then obtain sharp lower bounds on the necessary intra-cluster repair BW to achieve optimal trade-off. Our bounds reveal the interesting fact that, while it is beneficial to increase the number of local helper nodes $\ell$ in order to improve the storage-vs-inter-cluster-repair-BW trade-off, increasing $\ell$ not only increases intra-cluster BW in the host-cluster, but also increases the intra-cluster BW in the remote helper clusters. We also analyze resilience of the clustered storage system against passive eavesdropping by providing file-size bounds and optimal code constructions.

Control of Cognitive Networks With Friendly Jamming as a Service

We consider a cognitive radio network with single antenna primary user (PU), destination and eavesdropper, and multi-antenna secondary users (SUs). SUs act as helper nodes transmitting noise to confound a passive eavesdropper while nulling the interference leakage at the destination. The jamming helper nodes are non-altruistic, and they gain access to the primary network by aiding in the confidential transmissions of the PU. We obtain the secrecy outage probability as a closed-form expression when PU and SUs have merely statistical information about the eavesdropper channel. For the delay-unlimited system, we derive the achievable confidential rates given the control strategies for bandwidth and power allocation. For the more practical delay-limited case, we formulate a network control problem with secrecy appearing as a quality of service constraint optimizing the confidential and open transmission rates of the PU and SUs, respectively. Finally, we develop a dynamic control algorithm obtaining asymptotically optimal solution and demonstrate its performance by numerical experiments.