Chicago, Aug. 29, 2023 (GLOBE NEWSWIRE) -- The global Self-Healing Networks Market size to grow from USD 0.6 billion in 2022 to USD 2.4 billion by 2027, at a Compound Annual Growth Rate (CAGR) of 33.3% during the forecast period, according to a new report by MarketsandMarkets™. The Self-healing networks market is anticipated to increase in a rapid pace during the forecast period. A number of driving factors comprises of the need to handle and reducerising network traffic, growing demand of disruptive technologies such as AI and ML combined with self-healing, and rise in human error rates across legacy systems affecting network downtime.
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268 - Tables
59 - Figures
276 - Pages
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Scope of the Report
| Report Metrics | Details |
| Market size value in 2022 | USD 0.6 billion |
| Market size value in 2027 | USD 2.4 billion |
| Growth rate | CAGR of 33.3% |
| Market size available for years | 2019–2027 |
| Base year considered | 2021 |
| Forecast period | 2022–2027 |
| Forecast units | Value (USD) Million/Billion |
| Segments Covered | Component, Network Type, Organization Size, Deployment Mode, Application, Vertical and Region. |
| Geographies Covered | North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
| Companies Covered | Some of the significant Self-healing Networks Market vendors are Fortra (US), VMWare (US), IBM (US), CommScope (US), SolarWinds (US), ManageEngine (US), BMC Software (US) and many more. |
The self-healing network solution support users to manage network issues which are resolved without the need for humans to get involved. A self-healing network solutions can detect and remediate outages, failures, and breaches of all sorts. It is similar to mesh network technology for the vendor’s I/A Series automation platform uses commercial off-the-shelf Ethernet switches, ports and fiber optic media in advanced mesh configurations to offer multiple transmission paths between different network stations.
The self-healing networks component market is segmented based on solutions and services. Vendors offer self-healing networks solution in the form of software tools or platforms. The services segmentation included managed services and professional services. Further segmenting the professional services, self-healing networks includes consulting, system integration and implementation, and support and maintenance.
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The self-healing networks market by network type comprises of physical network, virtual network, and hybrid network. The components of network infrastructure are highly complex and varied with the presence of a number of critical physical and virtual edge devices, such as switches, routers, and firewalls, from various network hardware vendors. Self-healing networks solutions decrease the labor-intensive tasks and meet the increasing demand for automated, policy-driven changes and configuration management to support physical, virtual, and hybrid network environments
The self-healing networks market, by organization size, is segmented into large enterprises and SMEs. Large enterprises are expected to rapidly adopt self-healing networks solutions and services due to their complex network of channel partners present across the globe. The market share of large enterprises is currently higher; however, the market for SMEs is expected to increase at a higher growth rate in the coming years. SMEs prefer cloud-based deployment, as cloud-based solutions are cost-effective and easy to deploy (as cloud de ployment does not require dedicated IT staff). With the adoption of these solutions, small enterprises are able to collect and analyze data, thus improving customer services.
The self-healing networks market has been segmented by deployment mode into on-premises and cloud. Depending on their requirements, organizations can opt for one of these or a mix of the deployment modes. Currently, the market share of cloud deployment is higher; however, the market for on-premises deployment mode is expected to grow at a higher CAGR in the coming years. Currently, the demand for cloud-based solutions is growing over the on-premises counterparts, owing to the various advantages offered by the cloud deployment mode such as security and scalability.
The demand for self-healing networks is increasing as technology promises faster delivery of business insights as per the requirements of end users. Self-healing capabilities are implemented through distributed communication protocols that develop redundant links to recover the connectivity of the system. Noticeable applications of self-healing are in the important field of infrastructural networks like gas, power, water, oil distribution systems. The self-healing networks market, by application, comprises of network provisioning, network bandwidth monitoring, policy management, security compliance management, root cause analysis, network traffic management, network access control, and other applications (performance management, configuration management, and fault management).
The market is segmented into BFSI, telecom, retail and consumer goods, healthcare and life sciences, , IT and ITES, education, media and entertainment, and other verticals. The other verticals comprise energy and utilities, manufacturing, and government. The telecom vertical is the major revenue contributor to the self-healing networks market, whereas the healthcare and life sciences sector will gain traction in the coming years.
The self-healing networks market has been segmented into five regions: North America, Europe, Asia Pacific, the Middle East and Africa, and Latin America. Among these regions, North America is expected to hold the largest market size during the forecast period. The key factor supporting the growth of the self-healing networks market in North America is the growing need for self-healing networks technology to detect and remediate network outages, failures, and breaches. Additionally, the rising number of self-healing networks solution providers across regions is expected to drive the growth in the market. Asia Pacific is expected to grow at the highest CAGR during the forecast period. The self-healing networks market is expected to witness considerable developments and significant adoption owing to the need reduce network traffic and automate network remediation across Asia Pacific during the forecast period.
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Top Trends in Global Self-healing Networks Market
The global Self-healing Networks Market is growing rapidly, and there are a number of key trends that are driving this growth. Some of the top trends in the global Self-healing Networks Market include:
- Automation and Artificial Intelligence (AI): Self-healing networks are rapidly incorporating AI and machine learning algorithms to improve their capacity to recognise and address network problems in real-time. These technologies give networks the ability to foresee possible faults, take proactive corrective action, and improve network performance.
- 5G and Beyond: As 5G network deployment picked up steam, self-healing capabilities turned into a must to sustain the high dependability and low latency that 5G promised. A important trend to guarantee seamless connectivity was the incorporation of self-healing capabilities into 5G infrastructure.
- Edge Computing: Self-healing networks were being expanded to edge nodes with the emergence of edge computing, where data processing occurs closer to the data source. For numerous IoT applications and real-time data processing, dependable and durable connections at the edge were ensured by this trend.
- Self-healing networks were beginning to include self-healing technologies that were security-focused. This meant that networks may respond to security breaches by isolating vulnerable components and reducing the potential impact of cyberattacks, in addition to recovering from technical failures.
- Networks are evolving towards predictive analytics, which is looking at historical data to spot patterns and trends that may indicate future failures. Self-healing networks might resolve problems before they resulted in substantial disruptions by employing predictive analytics.
- Cross-Domain Self-Healing: Creating self-healing methods that span several domains or network layers has become more popular than concentrating on specific network domains. With this comprehensive strategy, network performance and resilience were to be maximised throughout the entire ecosystem.
- Networks that work together to solve problems are known as collaborative networks. These networks are researching the idea of collaborative self-healing. Sharing information on errors, traffic patterns, and other pertinent data may be a part of this.
- Self-healing networks were also evolving in terms of energy efficiency. By turning off or decreasing the power of specific components when not in use, they were created to dynamically optimise power usage, resulting in cost savings and environmental sustainability.
- Vendor Solutions: A range of technology companies were providing self-healing network solutions for various sectors of the economy and use cases. Self-healing technologies were developing as a result of increased market competition.
Key Industry Development
The Self-healing Networks Market is constantly evolving, with new technologies and solutions emerging all the time. Here are some of the key industry developments that are shaping the market:
- Partnerships and Collaborations: To create and implement self-healing network solutions, numerous technology companies, telecommunications corporations, and network infrastructure suppliers were collaborating and forming partnerships. The goal of these partnerships was to pool knowledge from several fields to develop self-healing systems that are more reliable and efficient.
- AI and Advanced Machine Learning: The incorporation of AI and Advanced Machine Learning into self-healing networks was a key advancement. With the use of these technologies, networks might instantly analyse vast volumes of data, foresee future problems, and take preventative measures to avoid interruptions.
- Self-healing techniques were being expanded to edge devices and nodes with the development of edge computing. In edge computing contexts, this facilitated quicker responses to local network problems and enhanced overall system resilience.
- Security-Focused Self-Healing: Mechanisms for self-healing are developing to solve both technical and security flaws. This required identifying unauthorised access, isolating compromised components, and minimising the effects of cyberattacks on the network.
- Integration with SDN and NFV: The networking landscape was increasingly dominated by Software-Defined Networking (SDN) and Network Functions Virtualization (NFV). These technologies were being enhanced with self-healing capabilities to improve the automation and management of network resources.
- Hybrid and Multi-Cloud Environments: Self-healing networks were changing to work smoothly across various cloud platforms and on-premises infrastructure as organisations adopted hybrid and multi-cloud strategies. The goal of this development was to guarantee dependability and constant performance in challenging cloud environments.
- Industry associations and standardisation organisations were attempting to establish common frameworks and standards for self-healing networks. The adoption of self-healing systems was facilitated by standardisation, which helped to ensure interoperability between solutions from various providers.
- Real-Time Analytics: This was a big development, with a focus on real-time data analytics. In order to maintain service, self-healing networks used analytics to track network health, spot anomalies, and set off automatic responses.
- Focus on Redundancy and Resilience: The design of resilient and resilient network topologies was given more attention in self-healing networks. To reduce downtime, this included creating networks with failover features and alternative routes.
- Energy Efficiency: To reduce the amount of energy used by network components, energy-efficient self-healing techniques were being created. This change decreased operational expenses and was in line with more general environmental initiatives.
- Case Studies and Success Stories: As the market for self-healing networks developed, there were more case studies and success stories from the real world demonstrating the advantages of using self-healing mechanisms. By highlighting real commercial value, these examples promoted adoption.
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