Service Proxies: Roles & Mechanisms

• Service proxies are intermediary components that transparently relay and transform communication by applying protocol translation, caching, and policy enforcement.
• They are deployed across IoT, microservices, and HPC environments to enhance security, control, and resource optimization while bridging heterogeneous network domains.
• Empirical evaluations show that service proxies can reduce latency, boost throughput, and improve energy efficiency, though they introduce trade-offs in performance and security.

A service proxy is an intermediary component that transparently relays, transforms, or manages communication between clients and servers, often incorporating policy enforcement, protocol translation, caching, security, or resource optimization. They are foundational elements in modern distributed systems, cloud-native architectures, IoT deployments, and web services, bridging heterogeneity across network domains, enhancing control and observability, and isolating resource-constrained or high-value targets.

1. Architectural Patterns and Roles

Service proxies appear in multiple architectural forms, each optimized for a specific placement in the communication path and a distinct set of control and data-plane responsibilities.

• IoT Edge Proxies: In IoT-Fog networks, lightweight proxies terminate local CoAP/UDP/IPv6 domains of sensor nodes and present an HTTP/TCP/IPv4(6) interface to external datacenters or clients. These proxies cache sensor readings, translate between serialization formats (e.g., EXI↔XML), and implement data aggregation or pre-processing, scaling to thousands of endpoints via hierarchical organization (Misic et al., 2018).
• Sidecar Proxies in Microservices: In service meshes, a dedicated proxy (often Envoy) is instantiated alongside each application container (the "sidecar" pattern), intercepting all ingress and egress traffic. This decouples cross-cutting policy (mTLS, RBAC, traffic shaping, telemetry) from business logic and centralizes control via a distributed configuration plane (Sahu et al., 2023).
• Overlay and Tunneled Proxies: Overlays like Hermes construct multi-hop proxy chains that delegate networking and policy from endpoints into a reconfigurable proxy substrate. Proxies are stratified into Dependent Proxies ("DP", at endpoint edges) and Standalone Proxies ("SaP", within overlay cores), using unified tunneling substrates (e.g., HTTP CONNECT, MASQUE) to traverse heterogeneous networks (Farkiani et al., 20 Nov 2024).
• Reverse Proxies and Gateways: In traditional web and HPC settings, reverse proxies terminate client connections and securely route to backend application instances. Satellite (SDSC) exemplifies this with a token-authenticated HTTPS reverse proxy for Jupyter Notebooks, providing secure, single-URL access in multi-tenant clusters (Thomas et al., 3 Nov 2025).
• Protocol-Specific Proxies: Domain-tailored proxies (e.g., MLProxy for ML inference workloads on serverless platforms) implement adaptive request batching and SLA-driven scheduling as an intelligent reverse proxy in front of backend stateless services (Mahmoudi et al., 2022).

The diversity of roles is summarized below:

Placement	Primary Functions	Example References
Edge (IoT/CoRE)	Protocol translation, caching, resource protection	(Misic et al., 2018, Amsüss, 2022)
Pod/Container Sidecar	Security, routing, telemetry, policy enforcement	(Sahu et al., 2023, Li et al., 2023)
Overlay/Core Proxy	Multi-domain routing, tunnel encapsulation, failover	(Farkiani et al., 20 Nov 2024)
Reverse/Ingress Proxy	Authentication, access control, session multiplexing	(Thomas et al., 3 Nov 2025, Mahmoudi et al., 2022)
Application/Object Proxy	Decoupled reference, data mediation (ProxyStore)	(Pauloski et al., 2023)

2. Core Functionalities and Mechanisms

Service proxies implement a wide range of functionalities that extend beyond simple request forwarding:

• Protocol and Data Format Translation: IoT proxies natively bridge CoAP/UDP to HTTP/TCP, converting between EXI (binary XML) and XML, or similarly, overlay proxies encapsulate UDP/TCP/IP packets within HTTP2/3 tunnels (Misic et al., 2018, Farkiani et al., 20 Nov 2024).
• Caching and Freshness Enforcement: Edge proxies maintain caches of resource representations, balancing proactive (timer-driven) and reactive (on-demand) refetching. The freshness model applies $F(t) = \max[0,\,\mathrm{MaxAge}-(t-t_0)]$, with $\mathrm{MaxAge}$ sourced from server metadata or estimated statistically; e.g., $\mathrm{MaxAge} \approx \mu + k\sigma$ for event-driven resources (Misic et al., 2018).
• Policy Enforcement and Observability: Sidecars and managed proxies (e.g., mRPC) apply filters, access control, rate-limiting, and telemetry at L4–L7. Policies are dynamically loaded and may operate on high-level arguments prior to serialization, minimizing redundant marshaling/unmarshaling (Chen et al., 2023, Sahu et al., 2023).
• Security and Isolation: Authentication proxies employ hardware roots of trust (TPM DRTM/TXT, sealed storage, remote attestation) to guarantee that credentials or secrets remain cryptographically protected even under full software compromise (Uzunay et al., 2015). Isolation in DPU-centric proxies physically separates mesh governance from tenant logic (Li et al., 2023).
• Resource Mediation and Protection: Guard proxies in CoRE automatically rate-limit or outright block traffic to resource-constrained devices, enforcing accept-lists or token-based tunnels to prevent exhaustion attacks (Amsüss, 2022).
• Batching and Scheduling: Adaptive proxies for ML inference dynamically tune batch size and scheduling window to minimize cost and mean response time subject to SLOs, using empirically observed per-batch latency distributions, rather than static queuing models (Mahmoudi et al., 2022).

3. Performance, Security, and Resource Trade-offs

Proxy deployment introduces a spectrum of trade-offs across latency, bandwidth, energy consumption, robustness, and security.

• Performance Overhead: Sidecar proxies introduce user-visible latency overhead, which scales with policy complexity (e.g., filter chains, header modifications, RBAC lists). Cache-miss penalties and L2 cache pressure dominate microarchitectural bottlenecks at higher policy counts (Sahu et al., 2023). FlatProxy, a DPU-based service mesh proxy, reduces L4 latency by ≈90% and increases throughput by 4×–8× over Envoy by offloading data plane logic to DPU hardware (Li et al., 2023).
• Resource Efficiency: In IoT, group-based proxy designs (MGET) achieve higher data transmission success rates (0.96–0.98) and lower per-node energy (<0.25 J/day at $N=500$) than unicast polling (Misic et al., 2018). Minimalist unikernel proxies (Miniproxy) require as little as 6 MB RAM and boot in ≈12 ms, enabling just-in-time instantiation at the edge with connection handling at >1.5 Gb/s (Siracusano et al., 2016).
• Stability and Vulnerability: Free web proxies are highly unstable (only 34.5% ever active; 3.36% active daily) and exhibit high rates of security vulnerabilities (39.4% with unauthorized RCE, 45.7% privilege escalation among 4,452 CVEs) (Mehanna et al., 4 Mar 2024).
• Security Model: Proxies acting as authentication or credential stores require formal chain-of-trust bootstrapping with hardware attestation (TPM DRTM, PCR-based sealing), splitting responsibility for envelope encryption/decryption, session key derivation, and remote attestation validation (Uzunay et al., 2015).

4. Discovery, Placement, and Reconfiguration Strategies

Proxy architecture determines both their discovery/announcement and dynamic placement or adaptation logic.

• Discovery via Resource Directory/DNS-SD: In CoRE, proxies can be discovered by clients through link-format entries in resource directories or DNS-SD registration. Optionally, OSCORE/EDHOC protocol extensions allow in-band discovery and negotiation via CoAP Option "Echo" (Amsüss, 2022).
• Placement Costs: Hermes overlays select sets of proxies to minimize total cost under placement constraints. The total cost function incorporates hosting cost $C_{\mathrm{host}}(p)$, latency $L(p)$, and utilization $U(p)$, weighted by operator-defined coefficients:

$$C_{\mathrm{total}} = \sum_{p\in \mathcal{P}} \left( C_{\mathrm{host}}(p) + w_1 L(p) + w_2 U(p) \right)$$

Reconfiguration triggers whenever thresholds on end-to-end latency $L$ or reliability $R$ are violated; the algorithm runs in $O(N\log N)$ (Farkiani et al., 20 Nov 2024).

• Elasticity and Instantiation: Miniproxy supports on-the-fly instantiation, booting unikernel proxies on demand at SYN-receive time, allowing in-path deployment chains that optimize for geographical or topological factors (Siracusano et al., 2016).
• Batch Scheduling and SLA Control: Adaptive proxies like MLProxy adjust batch size and dispatch timeouts using real-time feedback, applying additive-increase/multiplicative-decrease rules on $Max\_BS$ in response to observed latency or SLO violation deviation (Mahmoudi et al., 2022).

5. Use Cases and Empirical Evaluations

Service proxies underpin a broad array of practical systems and are empirically evaluated across heterogeneous contexts.

• IoT Hierarchies: Layered proxies allow IoT data to be cached, refreshed, and served at bounded staleness and energy cost across domains, with group-based query (MGET) and OBSERVE mechanisms dominating in scalability and efficiency (Misic et al., 2018).
• Multi-Domain Networking: Hermes enables seamless backward-compatible transport of TCP/UDP/IP, reliable data delivery under intermittent link failures, agile reconfiguration (e.g., moving tunnel endpoints to reduce RTT by 50 ms in <10 s), and policy-driven address virtualization (Farkiani et al., 20 Nov 2024).
• Decentralized Web Service Orchestration: Proxies attached to decentralized orchestration services locally perform token-based execution, service composition, mediation, and storage, reducing central bandwidth by nearly 50% and achieving empirical speedups of 1.3–1.4× in workflow execution (Jaradat et al., 2013).
• Federated Data Movement: Object proxies (ProxyStore) in Python enable pass-by-reference semantics for wide-area workflows, optimizing data movement by decoupling control flow from data flow, yielding 33–89% reductions in round-trip times for scientific applications (Pauloski et al., 2023).
• Reverse Proxy for HPC: SDSC Satellite provides Jupyter users with single-URL, HTTPS access to compute-node notebooks, handling dynamic port mapping and token-bound authentication through an Apache-based reverse proxy architecture (Thomas et al., 3 Nov 2025).

6. Security Risks, Challenges, and Best Practices

Security vulnerabilities and operational inefficiencies are major concerns:

• Exposure of Sensitive Traffic: Free proxies often lack encryption, enabling eavesdropping and modification (16,923 of 221,319 active proxies modify content at least once) (Mehanna et al., 4 Mar 2024). Web proxies in cellular networks may perform split-TCP, caching, and aggressive transcoding, not always respecting user expectations or application semantics (Zhang et al., 2015).
• Vulnerability Accumulation: Embedded hardware hosting proxies, such as MikroTik routers, are frequently left unpatched, with hundreds of reported CVEs including remote code execution flaws (Mehanna et al., 4 Mar 2024).
• Trust Anchors for Credential Proxies: The Trust-in-the-Middle architecture employs TPM-based remote attestation to guarantee that authentication proxies are operating untampered; only after remote attestation succeeds does the client send sensitive data, with all critical private keys and secrets sealed against measured PCR state (Uzunay et al., 2015).
• Best Practices: Operators are advised to select proxies with strong SLAs, enforce end-to-end encryption, engage in proactive vulnerability scanning, regularly patch software/firmware, limit open access, and log all transactions for forensic traceability (Mehanna et al., 4 Mar 2024). For sidecar proxies, assignment of dedicated CPU resources, filter-chain profiling including microarchitectural events, and minimization of complex filters in latency-sensitive paths are essential to optimize performance (Sahu et al., 2023).

7. Future Directions and Open Problems

Modern service proxies drive fundamental research questions and open systems challenges:

• Offload and Hardware Specialization: The move to DPU-centric service meshes promises line-rate, near-zero-latency proxies with security and observability guarantees exceeding host-based sidecars, posing new co-design challenges (Li et al., 2023).
• Formal Verification and Attestation: Secure proxy systems rely on formal chains of trust, TPM or TEE verification, and sealed storage, requiring advances in tool-supported verification for correct-by-construction isolation (Uzunay et al., 2015).
• Dynamic Policy Composition: Proxy architectures such as mRPC enable zero-downtime policy and transport upgrades at runtime, but introduce new trust surfaces, necessitating robust sandboxing and cross-application resource control (Chen et al., 2023).
• Proxy Discovery and Coordination: Dynamic, decentralized proxy systems (CoRE, overlay, federated workflows) hinge on standardized discovery, load balancing, state handover, and adaptive reconfiguration strategies, many of which remain areas of active exploration (Amsüss, 2022, Farkiani et al., 20 Nov 2024).
• Intelligent Scheduling and SLA Optimization: Adaptive proxies for ML and serverless environments increasingly employ empirical, measurement-driven controllers rather than static, closed-form models. Enhancing robustness, convergence speed, and explainability of these controllers remains an open area (Mahmoudi et al., 2022).
• Security, Privacy, and Trust: The persistent prevalence of vulnerable, malicious, or misconfigured free proxies and embedded proxy devices calls for improved auditability, reputation systems, and trusted execution infrastructures (Mehanna et al., 4 Mar 2024, Uzunay et al., 2015).

Service proxies are foundational to scalable, secure, and manageable distributed systems. They enable protocol bridging, enforce policies, optimize resources, and shield endpoints, but make visible the constant tension between control and performance, security and accessibility, and centralization and decentralization across digital infrastructure.